| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - emotion |
| base_model: bert-base-uncased |
| model-index: |
| - name: bert_emo_classifier |
| 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_emo_classifier |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2748 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.9063 | 0.25 | 500 | 0.4845 | |
| | 0.3362 | 0.5 | 1000 | 0.3492 | |
| | 0.2759 | 0.75 | 1500 | 0.2819 | |
| | 0.2521 | 1.0 | 2000 | 0.2464 | |
| | 0.1705 | 1.25 | 2500 | 0.2345 | |
| | 0.1841 | 1.5 | 3000 | 0.2013 | |
| | 0.1428 | 1.75 | 3500 | 0.1926 | |
| | 0.1747 | 2.0 | 4000 | 0.1866 | |
| | 0.1082 | 2.25 | 4500 | 0.2302 | |
| | 0.1142 | 2.5 | 5000 | 0.2118 | |
| | 0.1205 | 2.75 | 5500 | 0.2318 | |
| | 0.1135 | 3.0 | 6000 | 0.2306 | |
| | 0.0803 | 3.25 | 6500 | 0.2625 | |
| | 0.0745 | 3.5 | 7000 | 0.2850 | |
| | 0.085 | 3.75 | 7500 | 0.2719 | |
| | 0.0701 | 4.0 | 8000 | 0.2748 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.15.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.10.3 |
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|
