Commit
•
f389969
1
Parent(s):
c44c8a2
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,83 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- f1
|
| 7 |
+
model-index:
|
| 8 |
+
- name: distilbert-base-uncased_fold_1_binary
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# distilbert-base-uncased_fold_1_binary
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 1.1222
|
| 20 |
+
- F1: 0.7596
|
| 21 |
+
|
| 22 |
+
## Model description
|
| 23 |
+
|
| 24 |
+
More information needed
|
| 25 |
+
|
| 26 |
+
## Intended uses & limitations
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Training and evaluation data
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Training procedure
|
| 35 |
+
|
| 36 |
+
### Training hyperparameters
|
| 37 |
+
|
| 38 |
+
The following hyperparameters were used during training:
|
| 39 |
+
- learning_rate: 2e-05
|
| 40 |
+
- train_batch_size: 16
|
| 41 |
+
- eval_batch_size: 16
|
| 42 |
+
- seed: 42
|
| 43 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 44 |
+
- lr_scheduler_type: linear
|
| 45 |
+
- num_epochs: 25
|
| 46 |
+
|
| 47 |
+
### Training results
|
| 48 |
+
|
| 49 |
+
| Training Loss | Epoch | Step | Validation Loss | F1 |
|
| 50 |
+
|:-------------:|:-----:|:----:|:---------------:|:------:|
|
| 51 |
+
| No log | 1.0 | 288 | 0.4130 | 0.7517 |
|
| 52 |
+
| 0.3938 | 2.0 | 576 | 0.4260 | 0.7330 |
|
| 53 |
+
| 0.3938 | 3.0 | 864 | 0.5000 | 0.7488 |
|
| 54 |
+
| 0.19 | 4.0 | 1152 | 0.7415 | 0.7487 |
|
| 55 |
+
| 0.19 | 5.0 | 1440 | 0.8994 | 0.7397 |
|
| 56 |
+
| 0.0903 | 6.0 | 1728 | 0.9835 | 0.7386 |
|
| 57 |
+
| 0.0392 | 7.0 | 2016 | 1.1222 | 0.7596 |
|
| 58 |
+
| 0.0392 | 8.0 | 2304 | 1.2018 | 0.7314 |
|
| 59 |
+
| 0.0234 | 9.0 | 2592 | 1.2691 | 0.7330 |
|
| 60 |
+
| 0.0234 | 10.0 | 2880 | 1.2972 | 0.7496 |
|
| 61 |
+
| 0.0182 | 11.0 | 3168 | 1.4606 | 0.7492 |
|
| 62 |
+
| 0.0182 | 12.0 | 3456 | 1.4766 | 0.7361 |
|
| 63 |
+
| 0.006 | 13.0 | 3744 | 1.4888 | 0.7500 |
|
| 64 |
+
| 0.0057 | 14.0 | 4032 | 1.5684 | 0.7298 |
|
| 65 |
+
| 0.0057 | 15.0 | 4320 | 1.5354 | 0.7509 |
|
| 66 |
+
| 0.0058 | 16.0 | 4608 | 1.7733 | 0.7436 |
|
| 67 |
+
| 0.0058 | 17.0 | 4896 | 1.5695 | 0.7512 |
|
| 68 |
+
| 0.0089 | 18.0 | 5184 | 1.6593 | 0.7430 |
|
| 69 |
+
| 0.0089 | 19.0 | 5472 | 1.7092 | 0.7444 |
|
| 70 |
+
| 0.0048 | 20.0 | 5760 | 1.7206 | 0.7374 |
|
| 71 |
+
| 0.002 | 21.0 | 6048 | 1.7440 | 0.7343 |
|
| 72 |
+
| 0.002 | 22.0 | 6336 | 1.7582 | 0.7347 |
|
| 73 |
+
| 0.0006 | 23.0 | 6624 | 1.7294 | 0.7472 |
|
| 74 |
+
| 0.0006 | 24.0 | 6912 | 1.7454 | 0.7365 |
|
| 75 |
+
| 0.0001 | 25.0 | 7200 | 1.7395 | 0.7429 |
|
| 76 |
+
|
| 77 |
+
|
| 78 |
+
### Framework versions
|
| 79 |
+
|
| 80 |
+
- Transformers 4.21.0
|
| 81 |
+
- Pytorch 1.12.0+cu113
|
| 82 |
+
- Datasets 2.4.0
|
| 83 |
+
- Tokenizers 0.12.1
|