Upload 13 files
Browse files- README.md +446 -1
- all_results.json +15 -0
- config.json +26 -0
- eval_results.json +10 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +15 -0
- tokenizer.json +0 -0
- tokenizer_config.json +23 -0
- train_results.json +8 -0
- trainer_state.json +0 -0
- training_args.bin +3 -0
- vocab.json +0 -0
README.md
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| 1 |
---
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| 2 |
+
tags:
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| 3 |
+
- generated_from_trainer
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| 4 |
+
datasets:
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| 5 |
+
- tmp/cnn_clean_chatgpt_data/
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| 6 |
+
metrics:
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| 7 |
+
- accuracy
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| 8 |
+
model-index:
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| 9 |
+
- name: chatgpt-mlm
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+
results:
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| 11 |
+
- task:
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name: Masked Language Modeling
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+
type: fill-mask
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dataset:
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name: tmp/cnn_clean_chatgpt_data/
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+
type: tmp/cnn_clean_chatgpt_data/
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| 17 |
+
config: 1.0.0
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+
split: train
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args: 1.0.0
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+
metrics:
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| 21 |
+
- name: Accuracy
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+
type: accuracy
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+
value: 0.701455194792215
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| 24 |
---
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| 25 |
+
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| 26 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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| 28 |
+
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+
# chatgpt-mlm
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+
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+
This model is a fine-tuned version of [](https://huggingface.co/) on the tmp/cnn_clean_chatgpt_data/ dataset.
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+
It achieves the following results on the evaluation set:
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| 33 |
+
- Loss: 1.4969
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| 34 |
+
- Accuracy: 0.7015
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| 35 |
+
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+
## Model description
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| 37 |
+
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| 38 |
+
More information needed
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| 39 |
+
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| 40 |
+
## Intended uses & limitations
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| 41 |
+
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| 42 |
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More information needed
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| 43 |
+
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| 44 |
+
## Training and evaluation data
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| 45 |
+
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| 46 |
+
More information needed
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| 47 |
+
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| 48 |
+
## Training procedure
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| 49 |
+
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| 50 |
+
### Training hyperparameters
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| 51 |
+
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+
The following hyperparameters were used during training:
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| 53 |
+
- learning_rate: 5e-05
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| 54 |
+
- train_batch_size: 8
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| 55 |
+
- eval_batch_size: 8
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+
- seed: 42
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+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| 58 |
+
- lr_scheduler_type: linear
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+
- lr_scheduler_warmup_steps: 6
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| 60 |
+
- num_epochs: 75.0
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| 61 |
+
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+
### Training results
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| 63 |
+
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| 64 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| 65 |
+
|:-------------:|:-----:|:------:|:---------------:|:--------:|
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| 66 |
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| 7.2061 | 0.2 | 500 | 6.6958 | 0.1161 |
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| 67 |
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| 6.6051 | 0.4 | 1000 | 6.5527 | 0.1303 |
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| 68 |
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| 6.5016 | 0.6 | 1500 | 6.4720 | 0.1382 |
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| 69 |
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| 6.4189 | 0.8 | 2000 | 6.3796 | 0.1424 |
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| 70 |
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| 6.3648 | 1.0 | 2500 | 6.3224 | 0.1448 |
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| 6.2787 | 1.2 | 3000 | 6.2787 | 0.1411 |
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| 72 |
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| 6.2583 | 1.4 | 3500 | 6.2467 | 0.1446 |
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| 73 |
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| 6.2211 | 1.6 | 4000 | 6.2162 | 0.1475 |
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| 74 |
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| 6.1897 | 1.8 | 4500 | 6.1933 | 0.1466 |
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| 75 |
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| 6.1625 | 2.0 | 5000 | 6.1704 | 0.1483 |
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| 76 |
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| 6.1412 | 2.2 | 5500 | 6.1527 | 0.1484 |
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| 77 |
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| 6.1062 | 2.4 | 6000 | 6.1296 | 0.1492 |
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| 78 |
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| 6.1003 | 2.6 | 6500 | 6.1275 | 0.1483 |
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| 79 |
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| 6.0944 | 2.8 | 7000 | 6.0983 | 0.1496 |
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| 80 |
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| 6.077 | 3.0 | 7500 | 6.0839 | 0.1509 |
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| 81 |
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| 6.0419 | 3.2 | 8000 | 6.0747 | 0.1504 |
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| 82 |
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| 6.0264 | 3.4 | 8500 | 6.0729 | 0.1506 |
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| 83 |
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| 6.0222 | 3.6 | 9000 | 6.0585 | 0.1504 |
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| 84 |
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| 6.0067 | 3.8 | 9500 | 6.0518 | 0.1500 |
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| 6.0045 | 4.0 | 10000 | 6.0300 | 0.1504 |
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| 5.9659 | 4.2 | 10500 | 6.0248 | 0.1504 |
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| 87 |
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| 5.9542 | 4.4 | 11000 | 6.0143 | 0.1512 |
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| 88 |
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| 5.9479 | 4.6 | 11500 | 5.9891 | 0.1514 |
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| 89 |
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| 5.9506 | 4.8 | 12000 | 5.9827 | 0.1517 |
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| 5.9358 | 5.0 | 12500 | 5.9973 | 0.1509 |
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| 5.9114 | 5.2 | 13000 | 5.9761 | 0.1505 |
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| 92 |
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| 5.9089 | 5.4 | 13500 | 5.9637 | 0.1516 |
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| 93 |
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| 5.9008 | 5.6 | 14000 | 5.9535 | 0.1515 |
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| 5.9007 | 5.8 | 14500 | 5.9343 | 0.1530 |
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| 5.8734 | 6.0 | 15000 | 5.9255 | 0.1532 |
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| 96 |
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| 5.8519 | 6.2 | 15500 | 5.9213 | 0.1527 |
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| 97 |
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| 5.8383 | 6.4 | 16000 | 5.9126 | 0.1513 |
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| 98 |
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| 5.8461 | 6.6 | 16500 | 5.9041 | 0.1525 |
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| 99 |
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| 5.8387 | 6.8 | 17000 | 5.8923 | 0.1517 |
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| 5.831 | 7.0 | 17500 | 5.8782 | 0.1558 |
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| 5.8003 | 7.2 | 18000 | 5.8660 | 0.1554 |
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| 5.7832 | 7.4 | 18500 | 5.8508 | 0.1560 |
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| 103 |
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| 5.7902 | 7.6 | 19000 | 5.8495 | 0.1558 |
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| 104 |
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| 5.7707 | 7.8 | 19500 | 5.8376 | 0.1553 |
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| 105 |
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| 5.7638 | 8.0 | 20000 | 5.8289 | 0.1564 |
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| 5.741 | 8.2 | 20500 | 5.8230 | 0.1574 |
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| 107 |
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| 5.7291 | 8.4 | 21000 | 5.8110 | 0.1574 |
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| 108 |
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| 5.7206 | 8.6 | 21500 | 5.8014 | 0.1575 |
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| 5.6974 | 8.8 | 22000 | 5.7644 | 0.1605 |
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| 5.6954 | 9.0 | 22500 | 5.7404 | 0.1638 |
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| 5.6467 | 9.2 | 23000 | 5.7040 | 0.1668 |
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| 112 |
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| 5.6134 | 9.4 | 23500 | 5.6656 | 0.1738 |
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| 113 |
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| 5.5855 | 9.6 | 24000 | 5.6262 | 0.1787 |
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| 5.5374 | 9.8 | 24500 | 5.5587 | 0.1883 |
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| 5.4678 | 10.0 | 25000 | 5.4388 | 0.2009 |
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| 5.3324 | 10.2 | 25500 | 5.2703 | 0.2203 |
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| 5.1849 | 10.4 | 26000 | 5.0908 | 0.2434 |
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| 118 |
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| 5.0273 | 10.6 | 26500 | 4.9103 | 0.2657 |
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| 119 |
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| 4.8718 | 10.8 | 27000 | 4.7637 | 0.2844 |
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| 4.7523 | 11.0 | 27500 | 4.6064 | 0.3023 |
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| 4.5814 | 11.2 | 28000 | 4.4398 | 0.3220 |
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| 4.4627 | 11.4 | 28500 | 4.3005 | 0.3376 |
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| 4.3228 | 11.6 | 29000 | 4.1771 | 0.3520 |
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| 4.1885 | 11.8 | 29500 | 4.0783 | 0.3632 |
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| 4.0772 | 12.0 | 30000 | 3.9658 | 0.3765 |
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| 3.9602 | 12.2 | 30500 | 3.8686 | 0.3880 |
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| 3.8622 | 12.4 | 31000 | 3.7886 | 0.3968 |
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| 3.7958 | 12.6 | 31500 | 3.6968 | 0.4074 |
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| 3.7245 | 12.8 | 32000 | 3.6480 | 0.4129 |
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| 3.6503 | 13.0 | 32500 | 3.5771 | 0.4204 |
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| 3.5569 | 13.2 | 33000 | 3.5103 | 0.4286 |
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| 3.5151 | 13.4 | 33500 | 3.4611 | 0.4358 |
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| 3.4388 | 13.6 | 34000 | 3.4119 | 0.4410 |
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| 3.41 | 13.8 | 34500 | 3.3570 | 0.4486 |
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| 3.3447 | 14.0 | 35000 | 3.3158 | 0.4518 |
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| 3.2678 | 14.2 | 35500 | 3.2717 | 0.4585 |
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| 3.2395 | 14.4 | 36000 | 3.2234 | 0.4629 |
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| 3.2033 | 14.6 | 36500 | 3.1723 | 0.4697 |
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| 3.1739 | 14.8 | 37000 | 3.1409 | 0.4747 |
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| 3.1467 | 15.0 | 37500 | 3.1042 | 0.4782 |
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| 3.0736 | 15.2 | 38000 | 3.0561 | 0.4839 |
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| 142 |
+
| 3.0468 | 15.4 | 38500 | 3.0275 | 0.4869 |
|
| 143 |
+
| 3.0105 | 15.6 | 39000 | 3.0051 | 0.4898 |
|
| 144 |
+
| 2.9828 | 15.8 | 39500 | 2.9689 | 0.4950 |
|
| 145 |
+
| 2.9523 | 16.0 | 40000 | 2.9481 | 0.4959 |
|
| 146 |
+
| 2.8951 | 16.2 | 40500 | 2.8918 | 0.5039 |
|
| 147 |
+
| 2.8614 | 16.4 | 41000 | 2.8734 | 0.5054 |
|
| 148 |
+
| 2.8422 | 16.6 | 41500 | 2.8487 | 0.5083 |
|
| 149 |
+
| 2.8184 | 16.8 | 42000 | 2.8223 | 0.5138 |
|
| 150 |
+
| 2.7806 | 17.0 | 42500 | 2.7965 | 0.5167 |
|
| 151 |
+
| 2.7356 | 17.2 | 43000 | 2.7596 | 0.5209 |
|
| 152 |
+
| 2.7357 | 17.4 | 43500 | 2.7407 | 0.5250 |
|
| 153 |
+
| 2.7015 | 17.6 | 44000 | 2.7135 | 0.5272 |
|
| 154 |
+
| 2.688 | 17.8 | 44500 | 2.6935 | 0.5289 |
|
| 155 |
+
| 2.6582 | 18.0 | 45000 | 2.6572 | 0.5342 |
|
| 156 |
+
| 2.6186 | 18.2 | 45500 | 2.6396 | 0.5357 |
|
| 157 |
+
| 2.6071 | 18.4 | 46000 | 2.6270 | 0.5377 |
|
| 158 |
+
| 2.5891 | 18.6 | 46500 | 2.6110 | 0.5407 |
|
| 159 |
+
| 2.558 | 18.8 | 47000 | 2.5874 | 0.5435 |
|
| 160 |
+
| 2.5521 | 19.0 | 47500 | 2.5540 | 0.5465 |
|
| 161 |
+
| 2.5086 | 19.2 | 48000 | 2.5296 | 0.5504 |
|
| 162 |
+
| 2.4933 | 19.4 | 48500 | 2.5199 | 0.5523 |
|
| 163 |
+
| 2.4924 | 19.6 | 49000 | 2.5037 | 0.5550 |
|
| 164 |
+
| 2.4633 | 19.8 | 49500 | 2.4792 | 0.5567 |
|
| 165 |
+
| 2.4426 | 20.0 | 50000 | 2.4724 | 0.5600 |
|
| 166 |
+
| 2.4106 | 20.2 | 50500 | 2.4396 | 0.5626 |
|
| 167 |
+
| 2.4103 | 20.4 | 51000 | 2.4259 | 0.5631 |
|
| 168 |
+
| 2.3783 | 20.6 | 51500 | 2.4072 | 0.5672 |
|
| 169 |
+
| 2.3712 | 20.8 | 52000 | 2.4055 | 0.5679 |
|
| 170 |
+
| 2.3616 | 21.0 | 52500 | 2.3781 | 0.5724 |
|
| 171 |
+
| 2.3274 | 21.2 | 53000 | 2.3627 | 0.5746 |
|
| 172 |
+
| 2.3133 | 21.4 | 53500 | 2.3586 | 0.5751 |
|
| 173 |
+
| 2.3076 | 21.6 | 54000 | 2.3207 | 0.5785 |
|
| 174 |
+
| 2.2991 | 21.8 | 54500 | 2.3152 | 0.5796 |
|
| 175 |
+
| 2.2831 | 22.0 | 55000 | 2.3001 | 0.5815 |
|
| 176 |
+
| 2.2461 | 22.2 | 55500 | 2.2944 | 0.5822 |
|
| 177 |
+
| 2.2467 | 22.4 | 56000 | 2.2849 | 0.5856 |
|
| 178 |
+
| 2.2199 | 22.6 | 56500 | 2.2776 | 0.5863 |
|
| 179 |
+
| 2.2279 | 22.8 | 57000 | 2.2577 | 0.5885 |
|
| 180 |
+
| 2.2048 | 23.0 | 57500 | 2.2566 | 0.5886 |
|
| 181 |
+
| 2.1704 | 23.2 | 58000 | 2.2453 | 0.5914 |
|
| 182 |
+
| 2.1682 | 23.4 | 58500 | 2.2314 | 0.5927 |
|
| 183 |
+
| 2.1592 | 23.6 | 59000 | 2.2097 | 0.5961 |
|
| 184 |
+
| 2.1547 | 23.8 | 59500 | 2.1984 | 0.5972 |
|
| 185 |
+
| 2.1558 | 24.0 | 60000 | 2.1866 | 0.5993 |
|
| 186 |
+
| 2.1189 | 24.2 | 60500 | 2.1675 | 0.6009 |
|
| 187 |
+
| 2.1088 | 24.4 | 61000 | 2.1613 | 0.6028 |
|
| 188 |
+
| 2.1164 | 24.6 | 61500 | 2.1531 | 0.6046 |
|
| 189 |
+
| 2.094 | 24.8 | 62000 | 2.1507 | 0.6041 |
|
| 190 |
+
| 2.0977 | 25.0 | 62500 | 2.1299 | 0.6063 |
|
| 191 |
+
| 2.0657 | 25.2 | 63000 | 2.1218 | 0.6071 |
|
| 192 |
+
| 2.051 | 25.4 | 63500 | 2.1233 | 0.6083 |
|
| 193 |
+
| 2.0482 | 25.6 | 64000 | 2.1069 | 0.6100 |
|
| 194 |
+
| 2.04 | 25.8 | 64500 | 2.0985 | 0.6120 |
|
| 195 |
+
| 2.0341 | 26.0 | 65000 | 2.0929 | 0.6128 |
|
| 196 |
+
| 2.0207 | 26.2 | 65500 | 2.0767 | 0.6151 |
|
| 197 |
+
| 2.0044 | 26.4 | 66000 | 2.0672 | 0.6162 |
|
| 198 |
+
| 2.0037 | 26.6 | 66500 | 2.0623 | 0.6159 |
|
| 199 |
+
| 2.0081 | 26.8 | 67000 | 2.0614 | 0.6164 |
|
| 200 |
+
| 1.9847 | 27.0 | 67500 | 2.0499 | 0.6186 |
|
| 201 |
+
| 1.9465 | 27.2 | 68000 | 2.0399 | 0.6200 |
|
| 202 |
+
| 1.9573 | 27.4 | 68500 | 2.0353 | 0.6210 |
|
| 203 |
+
| 1.9682 | 27.6 | 69000 | 2.0187 | 0.6227 |
|
| 204 |
+
| 1.9573 | 27.8 | 69500 | 2.0251 | 0.6229 |
|
| 205 |
+
| 1.9491 | 28.0 | 70000 | 2.0086 | 0.6245 |
|
| 206 |
+
| 1.903 | 28.2 | 70500 | 2.0067 | 0.6246 |
|
| 207 |
+
| 1.9152 | 28.4 | 71000 | 1.9929 | 0.6264 |
|
| 208 |
+
| 1.9188 | 28.6 | 71500 | 1.9857 | 0.6274 |
|
| 209 |
+
| 1.9232 | 28.8 | 72000 | 1.9796 | 0.6287 |
|
| 210 |
+
| 1.9011 | 29.0 | 72500 | 1.9791 | 0.6289 |
|
| 211 |
+
| 1.8733 | 29.2 | 73000 | 1.9700 | 0.6289 |
|
| 212 |
+
| 1.8731 | 29.4 | 73500 | 1.9584 | 0.6303 |
|
| 213 |
+
| 1.8812 | 29.6 | 74000 | 1.9573 | 0.6323 |
|
| 214 |
+
| 1.8674 | 29.8 | 74500 | 1.9501 | 0.6318 |
|
| 215 |
+
| 1.8572 | 30.0 | 75000 | 1.9454 | 0.6333 |
|
| 216 |
+
| 1.849 | 30.2 | 75500 | 1.9375 | 0.6352 |
|
| 217 |
+
| 1.8332 | 30.4 | 76000 | 1.9344 | 0.6343 |
|
| 218 |
+
| 1.8413 | 30.6 | 76500 | 1.9293 | 0.6340 |
|
| 219 |
+
| 1.8298 | 30.8 | 77000 | 1.9228 | 0.6371 |
|
| 220 |
+
| 1.8336 | 31.0 | 77500 | 1.9215 | 0.6372 |
|
| 221 |
+
| 1.8122 | 31.2 | 78000 | 1.9133 | 0.6387 |
|
| 222 |
+
| 1.8001 | 31.4 | 78500 | 1.9119 | 0.6383 |
|
| 223 |
+
| 1.7934 | 31.6 | 79000 | 1.9088 | 0.6387 |
|
| 224 |
+
| 1.8079 | 31.8 | 79500 | 1.8940 | 0.6417 |
|
| 225 |
+
| 1.8017 | 32.0 | 80000 | 1.8889 | 0.6410 |
|
| 226 |
+
| 1.7789 | 32.2 | 80500 | 1.8883 | 0.6423 |
|
| 227 |
+
| 1.7739 | 32.4 | 81000 | 1.8836 | 0.6419 |
|
| 228 |
+
| 1.7602 | 32.6 | 81500 | 1.8795 | 0.6433 |
|
| 229 |
+
| 1.7731 | 32.8 | 82000 | 1.8769 | 0.6439 |
|
| 230 |
+
| 1.7784 | 33.0 | 82500 | 1.8590 | 0.6467 |
|
| 231 |
+
| 1.7506 | 33.2 | 83000 | 1.8664 | 0.6447 |
|
| 232 |
+
| 1.7307 | 33.4 | 83500 | 1.8553 | 0.6472 |
|
| 233 |
+
| 1.748 | 33.6 | 84000 | 1.8523 | 0.6470 |
|
| 234 |
+
| 1.7285 | 33.8 | 84500 | 1.8397 | 0.6491 |
|
| 235 |
+
| 1.7426 | 34.0 | 85000 | 1.8321 | 0.6492 |
|
| 236 |
+
| 1.7128 | 34.2 | 85500 | 1.8220 | 0.6507 |
|
| 237 |
+
| 1.7155 | 34.4 | 86000 | 1.8487 | 0.6479 |
|
| 238 |
+
| 1.7143 | 34.6 | 86500 | 1.8267 | 0.6504 |
|
| 239 |
+
| 1.7197 | 34.8 | 87000 | 1.8368 | 0.6499 |
|
| 240 |
+
| 1.7043 | 35.0 | 87500 | 1.8128 | 0.6524 |
|
| 241 |
+
| 1.6931 | 35.2 | 88000 | 1.8212 | 0.6517 |
|
| 242 |
+
| 1.6873 | 35.4 | 88500 | 1.8110 | 0.6531 |
|
| 243 |
+
| 1.684 | 35.6 | 89000 | 1.8145 | 0.6529 |
|
| 244 |
+
| 1.6802 | 35.8 | 89500 | 1.8046 | 0.6537 |
|
| 245 |
+
| 1.6807 | 36.0 | 90000 | 1.8016 | 0.6550 |
|
| 246 |
+
| 1.6612 | 36.2 | 90500 | 1.7997 | 0.6539 |
|
| 247 |
+
| 1.6586 | 36.4 | 91000 | 1.8014 | 0.6537 |
|
| 248 |
+
| 1.658 | 36.6 | 91500 | 1.7938 | 0.6565 |
|
| 249 |
+
| 1.6623 | 36.8 | 92000 | 1.7776 | 0.6586 |
|
| 250 |
+
| 1.6618 | 37.0 | 92500 | 1.7884 | 0.6573 |
|
| 251 |
+
| 1.6453 | 37.2 | 93000 | 1.7871 | 0.6571 |
|
| 252 |
+
| 1.6462 | 37.4 | 93500 | 1.7781 | 0.6585 |
|
| 253 |
+
| 1.6353 | 37.6 | 94000 | 1.7808 | 0.6583 |
|
| 254 |
+
| 1.6507 | 37.8 | 94500 | 1.7666 | 0.6603 |
|
| 255 |
+
| 1.6383 | 38.0 | 95000 | 1.7624 | 0.6606 |
|
| 256 |
+
| 1.6299 | 38.2 | 95500 | 1.7653 | 0.6605 |
|
| 257 |
+
| 1.6085 | 38.4 | 96000 | 1.7523 | 0.6610 |
|
| 258 |
+
| 1.6155 | 38.6 | 96500 | 1.7521 | 0.6612 |
|
| 259 |
+
| 1.6106 | 38.8 | 97000 | 1.7634 | 0.6605 |
|
| 260 |
+
| 1.6201 | 39.0 | 97500 | 1.7461 | 0.6625 |
|
| 261 |
+
| 1.5835 | 39.2 | 98000 | 1.7505 | 0.6617 |
|
| 262 |
+
| 1.5885 | 39.4 | 98500 | 1.7477 | 0.6623 |
|
| 263 |
+
| 1.5988 | 39.6 | 99000 | 1.7445 | 0.6635 |
|
| 264 |
+
| 1.6013 | 39.8 | 99500 | 1.7407 | 0.6637 |
|
| 265 |
+
| 1.594 | 40.0 | 100000 | 1.7336 | 0.6656 |
|
| 266 |
+
| 1.5741 | 40.2 | 100500 | 1.7348 | 0.6637 |
|
| 267 |
+
| 1.5744 | 40.4 | 101000 | 1.7242 | 0.6653 |
|
| 268 |
+
| 1.5809 | 40.6 | 101500 | 1.7262 | 0.6661 |
|
| 269 |
+
| 1.5723 | 40.8 | 102000 | 1.7257 | 0.6665 |
|
| 270 |
+
| 1.5695 | 41.0 | 102500 | 1.7182 | 0.6664 |
|
| 271 |
+
| 1.5462 | 41.2 | 103000 | 1.7257 | 0.6660 |
|
| 272 |
+
| 1.5545 | 41.4 | 103500 | 1.7101 | 0.6686 |
|
| 273 |
+
| 1.5574 | 41.6 | 104000 | 1.7108 | 0.6684 |
|
| 274 |
+
| 1.5485 | 41.8 | 104500 | 1.7164 | 0.6665 |
|
| 275 |
+
| 1.5487 | 42.0 | 105000 | 1.7080 | 0.6694 |
|
| 276 |
+
| 1.5278 | 42.2 | 105500 | 1.7092 | 0.6686 |
|
| 277 |
+
| 1.5282 | 42.4 | 106000 | 1.7052 | 0.6690 |
|
| 278 |
+
| 1.5468 | 42.6 | 106500 | 1.7058 | 0.6704 |
|
| 279 |
+
| 1.5375 | 42.8 | 107000 | 1.7020 | 0.6689 |
|
| 280 |
+
| 1.5301 | 43.0 | 107500 | 1.6950 | 0.6710 |
|
| 281 |
+
| 1.5224 | 43.2 | 108000 | 1.6990 | 0.6702 |
|
| 282 |
+
| 1.5105 | 43.4 | 108500 | 1.6919 | 0.6715 |
|
| 283 |
+
| 1.5179 | 43.6 | 109000 | 1.6845 | 0.6724 |
|
| 284 |
+
| 1.518 | 43.8 | 109500 | 1.6838 | 0.6721 |
|
| 285 |
+
| 1.5191 | 44.0 | 110000 | 1.6877 | 0.6715 |
|
| 286 |
+
| 1.4984 | 44.2 | 110500 | 1.6923 | 0.6712 |
|
| 287 |
+
| 1.5051 | 44.4 | 111000 | 1.6842 | 0.6722 |
|
| 288 |
+
| 1.4993 | 44.6 | 111500 | 1.6768 | 0.6741 |
|
| 289 |
+
| 1.5035 | 44.8 | 112000 | 1.6817 | 0.6727 |
|
| 290 |
+
| 1.5047 | 45.0 | 112500 | 1.6728 | 0.6733 |
|
| 291 |
+
| 1.4788 | 45.2 | 113000 | 1.6825 | 0.6720 |
|
| 292 |
+
| 1.4841 | 45.4 | 113500 | 1.6770 | 0.6735 |
|
| 293 |
+
| 1.4863 | 45.6 | 114000 | 1.6588 | 0.6753 |
|
| 294 |
+
| 1.4859 | 45.8 | 114500 | 1.6681 | 0.6741 |
|
| 295 |
+
| 1.4839 | 46.0 | 115000 | 1.6658 | 0.6740 |
|
| 296 |
+
| 1.4633 | 46.2 | 115500 | 1.6601 | 0.6765 |
|
| 297 |
+
| 1.4725 | 46.4 | 116000 | 1.6587 | 0.6753 |
|
| 298 |
+
| 1.4703 | 46.6 | 116500 | 1.6643 | 0.6756 |
|
| 299 |
+
| 1.4763 | 46.8 | 117000 | 1.6583 | 0.6759 |
|
| 300 |
+
| 1.4825 | 47.0 | 117500 | 1.6488 | 0.6766 |
|
| 301 |
+
| 1.4496 | 47.2 | 118000 | 1.6490 | 0.6772 |
|
| 302 |
+
| 1.457 | 47.4 | 118500 | 1.6462 | 0.6778 |
|
| 303 |
+
| 1.4541 | 47.6 | 119000 | 1.6368 | 0.6799 |
|
| 304 |
+
| 1.4561 | 47.8 | 119500 | 1.6404 | 0.6778 |
|
| 305 |
+
| 1.4547 | 48.0 | 120000 | 1.6385 | 0.6790 |
|
| 306 |
+
| 1.4406 | 48.2 | 120500 | 1.6374 | 0.6799 |
|
| 307 |
+
| 1.4374 | 48.4 | 121000 | 1.6319 | 0.6799 |
|
| 308 |
+
| 1.4395 | 48.6 | 121500 | 1.6425 | 0.6787 |
|
| 309 |
+
| 1.4347 | 48.8 | 122000 | 1.6252 | 0.6814 |
|
| 310 |
+
| 1.4392 | 49.0 | 122500 | 1.6360 | 0.6801 |
|
| 311 |
+
| 1.439 | 49.2 | 123000 | 1.6233 | 0.6826 |
|
| 312 |
+
| 1.4223 | 49.4 | 123500 | 1.6262 | 0.6809 |
|
| 313 |
+
| 1.4292 | 49.6 | 124000 | 1.6292 | 0.6811 |
|
| 314 |
+
| 1.4237 | 49.8 | 124500 | 1.6227 | 0.6812 |
|
| 315 |
+
| 1.4241 | 50.0 | 125000 | 1.6230 | 0.6810 |
|
| 316 |
+
| 1.4118 | 50.2 | 125500 | 1.6256 | 0.6822 |
|
| 317 |
+
| 1.4225 | 50.4 | 126000 | 1.6251 | 0.6817 |
|
| 318 |
+
| 1.4122 | 50.6 | 126500 | 1.6178 | 0.6827 |
|
| 319 |
+
| 1.4081 | 50.8 | 127000 | 1.6190 | 0.6813 |
|
| 320 |
+
| 1.4058 | 51.0 | 127500 | 1.6183 | 0.6836 |
|
| 321 |
+
| 1.3985 | 51.2 | 128000 | 1.6199 | 0.6817 |
|
| 322 |
+
| 1.3967 | 51.4 | 128500 | 1.6168 | 0.6829 |
|
| 323 |
+
| 1.4113 | 51.6 | 129000 | 1.6123 | 0.6832 |
|
| 324 |
+
| 1.3876 | 51.8 | 129500 | 1.6078 | 0.6841 |
|
| 325 |
+
| 1.4027 | 52.0 | 130000 | 1.6028 | 0.6847 |
|
| 326 |
+
| 1.3939 | 52.2 | 130500 | 1.6081 | 0.6845 |
|
| 327 |
+
| 1.391 | 52.4 | 131000 | 1.6034 | 0.6849 |
|
| 328 |
+
| 1.3895 | 52.6 | 131500 | 1.6016 | 0.6850 |
|
| 329 |
+
| 1.3858 | 52.8 | 132000 | 1.6010 | 0.6847 |
|
| 330 |
+
| 1.3852 | 53.0 | 132500 | 1.5886 | 0.6862 |
|
| 331 |
+
| 1.3716 | 53.2 | 133000 | 1.5964 | 0.6862 |
|
| 332 |
+
| 1.3727 | 53.4 | 133500 | 1.5952 | 0.6875 |
|
| 333 |
+
| 1.3656 | 53.6 | 134000 | 1.6031 | 0.6850 |
|
| 334 |
+
| 1.3873 | 53.8 | 134500 | 1.5927 | 0.6867 |
|
| 335 |
+
| 1.3742 | 54.0 | 135000 | 1.5970 | 0.6858 |
|
| 336 |
+
| 1.3687 | 54.2 | 135500 | 1.5954 | 0.6863 |
|
| 337 |
+
| 1.359 | 54.4 | 136000 | 1.5854 | 0.6873 |
|
| 338 |
+
| 1.3696 | 54.6 | 136500 | 1.5902 | 0.6878 |
|
| 339 |
+
| 1.38 | 54.8 | 137000 | 1.5870 | 0.6871 |
|
| 340 |
+
| 1.3529 | 55.0 | 137500 | 1.5888 | 0.6879 |
|
| 341 |
+
| 1.3479 | 55.2 | 138000 | 1.5720 | 0.6889 |
|
| 342 |
+
| 1.3558 | 55.4 | 138500 | 1.5810 | 0.6877 |
|
| 343 |
+
| 1.3565 | 55.6 | 139000 | 1.5687 | 0.6909 |
|
| 344 |
+
| 1.351 | 55.8 | 139500 | 1.5762 | 0.6897 |
|
| 345 |
+
| 1.3698 | 56.0 | 140000 | 1.5785 | 0.6881 |
|
| 346 |
+
| 1.3388 | 56.2 | 140500 | 1.5767 | 0.6882 |
|
| 347 |
+
| 1.3433 | 56.4 | 141000 | 1.5752 | 0.6896 |
|
| 348 |
+
| 1.3505 | 56.6 | 141500 | 1.5754 | 0.6890 |
|
| 349 |
+
| 1.3429 | 56.8 | 142000 | 1.5772 | 0.6896 |
|
| 350 |
+
| 1.337 | 57.0 | 142500 | 1.5732 | 0.6900 |
|
| 351 |
+
| 1.3398 | 57.2 | 143000 | 1.5681 | 0.6904 |
|
| 352 |
+
| 1.3334 | 57.4 | 143500 | 1.5696 | 0.6900 |
|
| 353 |
+
| 1.3384 | 57.6 | 144000 | 1.5674 | 0.6908 |
|
| 354 |
+
| 1.33 | 57.8 | 144500 | 1.5592 | 0.6916 |
|
| 355 |
+
| 1.327 | 58.0 | 145000 | 1.5498 | 0.6924 |
|
| 356 |
+
| 1.3234 | 58.2 | 145500 | 1.5626 | 0.6910 |
|
| 357 |
+
| 1.3266 | 58.4 | 146000 | 1.5743 | 0.6893 |
|
| 358 |
+
| 1.3152 | 58.6 | 146500 | 1.5680 | 0.6912 |
|
| 359 |
+
| 1.3279 | 58.8 | 147000 | 1.5581 | 0.6919 |
|
| 360 |
+
| 1.3172 | 59.0 | 147500 | 1.5645 | 0.6917 |
|
| 361 |
+
| 1.3073 | 59.2 | 148000 | 1.5579 | 0.6924 |
|
| 362 |
+
| 1.307 | 59.4 | 148500 | 1.5468 | 0.6939 |
|
| 363 |
+
| 1.3164 | 59.6 | 149000 | 1.5519 | 0.6930 |
|
| 364 |
+
| 1.3037 | 59.8 | 149500 | 1.5628 | 0.6917 |
|
| 365 |
+
| 1.3171 | 60.0 | 150000 | 1.5489 | 0.6934 |
|
| 366 |
+
| 1.3035 | 60.2 | 150500 | 1.5499 | 0.6931 |
|
| 367 |
+
| 1.3109 | 60.4 | 151000 | 1.5608 | 0.6922 |
|
| 368 |
+
| 1.304 | 60.6 | 151500 | 1.5612 | 0.6915 |
|
| 369 |
+
| 1.3104 | 60.8 | 152000 | 1.5511 | 0.6933 |
|
| 370 |
+
| 1.3071 | 61.0 | 152500 | 1.5469 | 0.6935 |
|
| 371 |
+
| 1.2935 | 61.2 | 153000 | 1.5485 | 0.6942 |
|
| 372 |
+
| 1.2866 | 61.4 | 153500 | 1.5463 | 0.6940 |
|
| 373 |
+
| 1.2926 | 61.6 | 154000 | 1.5406 | 0.6956 |
|
| 374 |
+
| 1.3029 | 61.8 | 154500 | 1.5424 | 0.6945 |
|
| 375 |
+
| 1.2921 | 62.0 | 155000 | 1.5446 | 0.6944 |
|
| 376 |
+
| 1.2765 | 62.2 | 155500 | 1.5397 | 0.6953 |
|
| 377 |
+
| 1.275 | 62.4 | 156000 | 1.5469 | 0.6945 |
|
| 378 |
+
| 1.2909 | 62.6 | 156500 | 1.5427 | 0.6945 |
|
| 379 |
+
| 1.2869 | 62.8 | 157000 | 1.5388 | 0.6949 |
|
| 380 |
+
| 1.2883 | 63.0 | 157500 | 1.5375 | 0.6948 |
|
| 381 |
+
| 1.2673 | 63.2 | 158000 | 1.5423 | 0.6948 |
|
| 382 |
+
| 1.2754 | 63.4 | 158500 | 1.5360 | 0.6957 |
|
| 383 |
+
| 1.2772 | 63.6 | 159000 | 1.5331 | 0.6952 |
|
| 384 |
+
| 1.283 | 63.8 | 159500 | 1.5354 | 0.6955 |
|
| 385 |
+
| 1.2737 | 64.0 | 160000 | 1.5388 | 0.6961 |
|
| 386 |
+
| 1.2681 | 64.2 | 160500 | 1.5382 | 0.6952 |
|
| 387 |
+
| 1.2769 | 64.4 | 161000 | 1.5350 | 0.6958 |
|
| 388 |
+
| 1.2668 | 64.6 | 161500 | 1.5345 | 0.6956 |
|
| 389 |
+
| 1.2795 | 64.8 | 162000 | 1.5198 | 0.6984 |
|
| 390 |
+
| 1.2632 | 65.0 | 162500 | 1.5324 | 0.6965 |
|
| 391 |
+
| 1.2646 | 65.2 | 163000 | 1.5420 | 0.6963 |
|
| 392 |
+
| 1.2739 | 65.4 | 163500 | 1.5308 | 0.6972 |
|
| 393 |
+
| 1.2667 | 65.6 | 164000 | 1.5220 | 0.6978 |
|
| 394 |
+
| 1.26 | 65.8 | 164500 | 1.5283 | 0.6961 |
|
| 395 |
+
| 1.2714 | 66.0 | 165000 | 1.5235 | 0.6977 |
|
| 396 |
+
| 1.2652 | 66.2 | 165500 | 1.5270 | 0.6973 |
|
| 397 |
+
| 1.2554 | 66.4 | 166000 | 1.5356 | 0.6959 |
|
| 398 |
+
| 1.2666 | 66.6 | 166500 | 1.5231 | 0.6968 |
|
| 399 |
+
| 1.2634 | 66.8 | 167000 | 1.5170 | 0.6994 |
|
| 400 |
+
| 1.2485 | 67.0 | 167500 | 1.5205 | 0.6988 |
|
| 401 |
+
| 1.2397 | 67.2 | 168000 | 1.5263 | 0.6982 |
|
| 402 |
+
| 1.2416 | 67.4 | 168500 | 1.5133 | 0.7001 |
|
| 403 |
+
| 1.2615 | 67.6 | 169000 | 1.5150 | 0.6990 |
|
| 404 |
+
| 1.254 | 67.8 | 169500 | 1.5213 | 0.6990 |
|
| 405 |
+
| 1.2463 | 68.0 | 170000 | 1.5157 | 0.6995 |
|
| 406 |
+
| 1.2412 | 68.2 | 170500 | 1.5082 | 0.7000 |
|
| 407 |
+
| 1.248 | 68.4 | 171000 | 1.5168 | 0.6992 |
|
| 408 |
+
| 1.2468 | 68.6 | 171500 | 1.5187 | 0.6991 |
|
| 409 |
+
| 1.246 | 68.8 | 172000 | 1.5094 | 0.7001 |
|
| 410 |
+
| 1.2443 | 69.0 | 172500 | 1.5186 | 0.6984 |
|
| 411 |
+
| 1.2451 | 69.2 | 173000 | 1.5157 | 0.6988 |
|
| 412 |
+
| 1.2375 | 69.4 | 173500 | 1.5102 | 0.7002 |
|
| 413 |
+
| 1.2441 | 69.6 | 174000 | 1.5143 | 0.7000 |
|
| 414 |
+
| 1.2335 | 69.8 | 174500 | 1.5173 | 0.6985 |
|
| 415 |
+
| 1.2361 | 70.0 | 175000 | 1.5102 | 0.7001 |
|
| 416 |
+
| 1.23 | 70.2 | 175500 | 1.5155 | 0.6997 |
|
| 417 |
+
| 1.2401 | 70.4 | 176000 | 1.5027 | 0.7005 |
|
| 418 |
+
| 1.2346 | 70.6 | 176500 | 1.5123 | 0.6995 |
|
| 419 |
+
| 1.2306 | 70.8 | 177000 | 1.5151 | 0.6984 |
|
| 420 |
+
| 1.2333 | 71.0 | 177500 | 1.5125 | 0.7000 |
|
| 421 |
+
| 1.2248 | 71.2 | 178000 | 1.5199 | 0.6992 |
|
| 422 |
+
| 1.2385 | 71.4 | 178500 | 1.5108 | 0.7000 |
|
| 423 |
+
| 1.2278 | 71.6 | 179000 | 1.5092 | 0.7000 |
|
| 424 |
+
| 1.2278 | 71.8 | 179500 | 1.5163 | 0.6989 |
|
| 425 |
+
| 1.2242 | 72.0 | 180000 | 1.5056 | 0.7010 |
|
| 426 |
+
| 1.2208 | 72.2 | 180500 | 1.4968 | 0.7023 |
|
| 427 |
+
| 1.2216 | 72.4 | 181000 | 1.5097 | 0.7006 |
|
| 428 |
+
| 1.2271 | 72.6 | 181500 | 1.4988 | 0.7013 |
|
| 429 |
+
| 1.2302 | 72.8 | 182000 | 1.5141 | 0.6997 |
|
| 430 |
+
| 1.2268 | 73.0 | 182500 | 1.4996 | 0.7016 |
|
| 431 |
+
| 1.2258 | 73.2 | 183000 | 1.5016 | 0.7008 |
|
| 432 |
+
| 1.2244 | 73.4 | 183500 | 1.5032 | 0.7012 |
|
| 433 |
+
| 1.2117 | 73.6 | 184000 | 1.5097 | 0.7003 |
|
| 434 |
+
| 1.2279 | 73.8 | 184500 | 1.5058 | 0.7012 |
|
| 435 |
+
| 1.2274 | 74.0 | 185000 | 1.5030 | 0.7015 |
|
| 436 |
+
| 1.2117 | 74.2 | 185500 | 1.5086 | 0.7008 |
|
| 437 |
+
| 1.2223 | 74.4 | 186000 | 1.4998 | 0.7018 |
|
| 438 |
+
| 1.227 | 74.6 | 186500 | 1.5059 | 0.7014 |
|
| 439 |
+
| 1.2168 | 74.8 | 187000 | 1.4984 | 0.7011 |
|
| 440 |
+
| 1.2093 | 75.0 | 187500 | 1.5077 | 0.7018 |
|
| 441 |
+
|
| 442 |
+
|
| 443 |
+
### Framework versions
|
| 444 |
+
|
| 445 |
+
- Transformers 4.25.1
|
| 446 |
+
- Pytorch 1.13.1+cu117
|
| 447 |
+
- Datasets 2.11.0
|
| 448 |
+
- Tokenizers 0.13.2
|
all_results.json
ADDED
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|
| 1 |
+
{
|
| 2 |
+
"epoch": 75.0,
|
| 3 |
+
"eval_accuracy": 0.701455194792215,
|
| 4 |
+
"eval_loss": 1.4969074726104736,
|
| 5 |
+
"eval_runtime": 232.9475,
|
| 6 |
+
"eval_samples": 5000,
|
| 7 |
+
"eval_samples_per_second": 21.464,
|
| 8 |
+
"eval_steps_per_second": 2.683,
|
| 9 |
+
"perplexity": 4.467850732884341,
|
| 10 |
+
"train_loss": 2.3812346901041668,
|
| 11 |
+
"train_runtime": 293209.3669,
|
| 12 |
+
"train_samples": 20000,
|
| 13 |
+
"train_samples_per_second": 5.116,
|
| 14 |
+
"train_steps_per_second": 0.639
|
| 15 |
+
}
|
config.json
ADDED
|
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|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"RobertaForMaskedLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_probs_dropout_prob": 0.1,
|
| 6 |
+
"bos_token_id": 0,
|
| 7 |
+
"classifier_dropout": null,
|
| 8 |
+
"eos_token_id": 2,
|
| 9 |
+
"hidden_act": "gelu",
|
| 10 |
+
"hidden_dropout_prob": 0.1,
|
| 11 |
+
"hidden_size": 768,
|
| 12 |
+
"initializer_range": 0.02,
|
| 13 |
+
"intermediate_size": 3072,
|
| 14 |
+
"layer_norm_eps": 1e-12,
|
| 15 |
+
"max_position_embeddings": 514,
|
| 16 |
+
"model_type": "roberta",
|
| 17 |
+
"num_attention_heads": 12,
|
| 18 |
+
"num_hidden_layers": 12,
|
| 19 |
+
"pad_token_id": 1,
|
| 20 |
+
"position_embedding_type": "absolute",
|
| 21 |
+
"torch_dtype": "float32",
|
| 22 |
+
"transformers_version": "4.25.1",
|
| 23 |
+
"type_vocab_size": 2,
|
| 24 |
+
"use_cache": true,
|
| 25 |
+
"vocab_size": 50265
|
| 26 |
+
}
|
eval_results.json
ADDED
|
@@ -0,0 +1,10 @@
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|
|
|
|
|
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|
|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 75.0,
|
| 3 |
+
"eval_accuracy": 0.701455194792215,
|
| 4 |
+
"eval_loss": 1.4969074726104736,
|
| 5 |
+
"eval_runtime": 232.9475,
|
| 6 |
+
"eval_samples": 5000,
|
| 7 |
+
"eval_samples_per_second": 21.464,
|
| 8 |
+
"eval_steps_per_second": 2.683,
|
| 9 |
+
"perplexity": 4.467850732884341
|
| 10 |
+
}
|
merges.txt
ADDED
|
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|
|
|
pytorch_model.bin
ADDED
|
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|
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|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9f350bd2256bb4a5e7ca9c888e9323f161b4311131001699ae896c3a78ac68a5
|
| 3 |
+
size 498866489
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
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|
|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": "<s>",
|
| 3 |
+
"cls_token": "<s>",
|
| 4 |
+
"eos_token": "</s>",
|
| 5 |
+
"mask_token": {
|
| 6 |
+
"content": "<mask>",
|
| 7 |
+
"lstrip": true,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false
|
| 11 |
+
},
|
| 12 |
+
"pad_token": "<pad>",
|
| 13 |
+
"sep_token": "</s>",
|
| 14 |
+
"unk_token": "<unk>"
|
| 15 |
+
}
|
tokenizer.json
ADDED
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tokenizer_config.json
ADDED
|
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|
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|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"bos_token": "<s>",
|
| 4 |
+
"cls_token": "<s>",
|
| 5 |
+
"eos_token": "</s>",
|
| 6 |
+
"errors": "replace",
|
| 7 |
+
"mask_token": {
|
| 8 |
+
"__type": "AddedToken",
|
| 9 |
+
"content": "<mask>",
|
| 10 |
+
"lstrip": true,
|
| 11 |
+
"normalized": false,
|
| 12 |
+
"rstrip": false,
|
| 13 |
+
"single_word": false
|
| 14 |
+
},
|
| 15 |
+
"model_max_length": 512,
|
| 16 |
+
"name_or_path": "chatgpt_tokenizer/",
|
| 17 |
+
"pad_token": "<pad>",
|
| 18 |
+
"sep_token": "</s>",
|
| 19 |
+
"special_tokens_map_file": null,
|
| 20 |
+
"tokenizer_class": "RobertaTokenizer",
|
| 21 |
+
"trim_offsets": true,
|
| 22 |
+
"unk_token": "<unk>"
|
| 23 |
+
}
|
train_results.json
ADDED
|
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| 1 |
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{
|
| 2 |
+
"epoch": 75.0,
|
| 3 |
+
"train_loss": 2.3812346901041668,
|
| 4 |
+
"train_runtime": 293209.3669,
|
| 5 |
+
"train_samples": 20000,
|
| 6 |
+
"train_samples_per_second": 5.116,
|
| 7 |
+
"train_steps_per_second": 0.639
|
| 8 |
+
}
|
trainer_state.json
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training_args.bin
ADDED
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9622e9d8fb015c7dd5186c4a8249458402d4bb66d08e920ead015b4a7f0acdb8
|
| 3 |
+
size 3451
|
vocab.json
ADDED
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|
|