| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: distilbert-base-uncased__subj__train-8-9 |
| 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. --> |
|
|
| # distilbert-base-uncased__subj__train-8-9 |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4865 |
| - Accuracy: 0.778 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 50 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.7024 | 1.0 | 3 | 0.6843 | 0.75 | |
| | 0.67 | 2.0 | 6 | 0.6807 | 0.5 | |
| | 0.6371 | 3.0 | 9 | 0.6677 | 0.5 | |
| | 0.585 | 4.0 | 12 | 0.6649 | 0.5 | |
| | 0.5122 | 5.0 | 15 | 0.6707 | 0.5 | |
| | 0.4379 | 6.0 | 18 | 0.6660 | 0.5 | |
| | 0.4035 | 7.0 | 21 | 0.6666 | 0.5 | |
| | 0.323 | 8.0 | 24 | 0.6672 | 0.5 | |
| | 0.2841 | 9.0 | 27 | 0.6534 | 0.5 | |
| | 0.21 | 10.0 | 30 | 0.6456 | 0.5 | |
| | 0.1735 | 11.0 | 33 | 0.6325 | 0.5 | |
| | 0.133 | 12.0 | 36 | 0.6214 | 0.5 | |
| | 0.0986 | 13.0 | 39 | 0.6351 | 0.5 | |
| | 0.081 | 14.0 | 42 | 0.6495 | 0.5 | |
| | 0.0638 | 15.0 | 45 | 0.6671 | 0.5 | |
| | 0.0449 | 16.0 | 48 | 0.7156 | 0.5 | |
| | 0.0399 | 17.0 | 51 | 0.7608 | 0.5 | |
| | 0.0314 | 18.0 | 54 | 0.7796 | 0.5 | |
| | 0.0243 | 19.0 | 57 | 0.7789 | 0.5 | |
| | 0.0227 | 20.0 | 60 | 0.7684 | 0.5 | |
| | 0.0221 | 21.0 | 63 | 0.7628 | 0.5 | |
| | 0.0192 | 22.0 | 66 | 0.7728 | 0.5 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.15.0 |
| - Pytorch 1.10.2+cu102 |
| - Datasets 1.18.2 |
| - Tokenizers 0.10.3 |
|
|
