|
--- |
|
license: apache-2.0 |
|
base_model: bert-large-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert-large-uncased-sst-2-32-13-smoothed |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# bert-large-uncased-sst-2-32-13-smoothed |
|
|
|
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6595 |
|
- Accuracy: 0.75 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 1e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 50 |
|
- num_epochs: 75 |
|
- label_smoothing_factor: 0.45 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 2 | 0.8178 | 0.5156 | |
|
| No log | 2.0 | 4 | 0.8133 | 0.5156 | |
|
| No log | 3.0 | 6 | 0.8065 | 0.5156 | |
|
| No log | 4.0 | 8 | 0.7961 | 0.5156 | |
|
| 0.8123 | 5.0 | 10 | 0.7821 | 0.5156 | |
|
| 0.8123 | 6.0 | 12 | 0.7655 | 0.5 | |
|
| 0.8123 | 7.0 | 14 | 0.7460 | 0.5 | |
|
| 0.8123 | 8.0 | 16 | 0.7247 | 0.5 | |
|
| 0.8123 | 9.0 | 18 | 0.7034 | 0.5312 | |
|
| 0.751 | 10.0 | 20 | 0.6892 | 0.5938 | |
|
| 0.751 | 11.0 | 22 | 0.6808 | 0.6094 | |
|
| 0.751 | 12.0 | 24 | 0.6761 | 0.6719 | |
|
| 0.751 | 13.0 | 26 | 0.6715 | 0.75 | |
|
| 0.751 | 14.0 | 28 | 0.6665 | 0.7812 | |
|
| 0.6479 | 15.0 | 30 | 0.6624 | 0.75 | |
|
| 0.6479 | 16.0 | 32 | 0.6615 | 0.7344 | |
|
| 0.6479 | 17.0 | 34 | 0.6572 | 0.7344 | |
|
| 0.6479 | 18.0 | 36 | 0.6529 | 0.7656 | |
|
| 0.6479 | 19.0 | 38 | 0.6503 | 0.7969 | |
|
| 0.5876 | 20.0 | 40 | 0.6499 | 0.7812 | |
|
| 0.5876 | 21.0 | 42 | 0.6496 | 0.7656 | |
|
| 0.5876 | 22.0 | 44 | 0.6502 | 0.7344 | |
|
| 0.5876 | 23.0 | 46 | 0.6536 | 0.75 | |
|
| 0.5876 | 24.0 | 48 | 0.6593 | 0.7344 | |
|
| 0.5439 | 25.0 | 50 | 0.6605 | 0.7344 | |
|
| 0.5439 | 26.0 | 52 | 0.6592 | 0.7344 | |
|
| 0.5439 | 27.0 | 54 | 0.6578 | 0.75 | |
|
| 0.5439 | 28.0 | 56 | 0.6575 | 0.75 | |
|
| 0.5439 | 29.0 | 58 | 0.6571 | 0.7344 | |
|
| 0.5429 | 30.0 | 60 | 0.6575 | 0.75 | |
|
| 0.5429 | 31.0 | 62 | 0.6635 | 0.75 | |
|
| 0.5429 | 32.0 | 64 | 0.6681 | 0.7344 | |
|
| 0.5429 | 33.0 | 66 | 0.6705 | 0.7188 | |
|
| 0.5429 | 34.0 | 68 | 0.6701 | 0.6875 | |
|
| 0.5404 | 35.0 | 70 | 0.6664 | 0.7188 | |
|
| 0.5404 | 36.0 | 72 | 0.6621 | 0.7344 | |
|
| 0.5404 | 37.0 | 74 | 0.6599 | 0.7344 | |
|
| 0.5404 | 38.0 | 76 | 0.6604 | 0.7344 | |
|
| 0.5404 | 39.0 | 78 | 0.6637 | 0.7344 | |
|
| 0.5403 | 40.0 | 80 | 0.6647 | 0.7344 | |
|
| 0.5403 | 41.0 | 82 | 0.6641 | 0.7344 | |
|
| 0.5403 | 42.0 | 84 | 0.6633 | 0.7344 | |
|
| 0.5403 | 43.0 | 86 | 0.6663 | 0.7344 | |
|
| 0.5403 | 44.0 | 88 | 0.6699 | 0.7344 | |
|
| 0.5406 | 45.0 | 90 | 0.6684 | 0.7344 | |
|
| 0.5406 | 46.0 | 92 | 0.6625 | 0.7344 | |
|
| 0.5406 | 47.0 | 94 | 0.6582 | 0.75 | |
|
| 0.5406 | 48.0 | 96 | 0.6549 | 0.75 | |
|
| 0.5406 | 49.0 | 98 | 0.6523 | 0.7656 | |
|
| 0.54 | 50.0 | 100 | 0.6523 | 0.75 | |
|
| 0.54 | 51.0 | 102 | 0.6525 | 0.75 | |
|
| 0.54 | 52.0 | 104 | 0.6531 | 0.75 | |
|
| 0.54 | 53.0 | 106 | 0.6534 | 0.75 | |
|
| 0.54 | 54.0 | 108 | 0.6539 | 0.75 | |
|
| 0.5396 | 55.0 | 110 | 0.6553 | 0.7656 | |
|
| 0.5396 | 56.0 | 112 | 0.6540 | 0.75 | |
|
| 0.5396 | 57.0 | 114 | 0.6555 | 0.7656 | |
|
| 0.5396 | 58.0 | 116 | 0.6565 | 0.7656 | |
|
| 0.5396 | 59.0 | 118 | 0.6588 | 0.7656 | |
|
| 0.5403 | 60.0 | 120 | 0.6609 | 0.75 | |
|
| 0.5403 | 61.0 | 122 | 0.6621 | 0.7344 | |
|
| 0.5403 | 62.0 | 124 | 0.6619 | 0.7344 | |
|
| 0.5403 | 63.0 | 126 | 0.6614 | 0.7344 | |
|
| 0.5403 | 64.0 | 128 | 0.6599 | 0.7344 | |
|
| 0.5405 | 65.0 | 130 | 0.6586 | 0.75 | |
|
| 0.5405 | 66.0 | 132 | 0.6583 | 0.7656 | |
|
| 0.5405 | 67.0 | 134 | 0.6580 | 0.7656 | |
|
| 0.5405 | 68.0 | 136 | 0.6582 | 0.75 | |
|
| 0.5405 | 69.0 | 138 | 0.6586 | 0.75 | |
|
| 0.5399 | 70.0 | 140 | 0.6591 | 0.75 | |
|
| 0.5399 | 71.0 | 142 | 0.6592 | 0.75 | |
|
| 0.5399 | 72.0 | 144 | 0.6592 | 0.75 | |
|
| 0.5399 | 73.0 | 146 | 0.6594 | 0.75 | |
|
| 0.5399 | 74.0 | 148 | 0.6594 | 0.75 | |
|
| 0.5403 | 75.0 | 150 | 0.6595 | 0.75 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.32.0.dev0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.13.3 |
|
|
