| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - emotion |
| metrics: |
| - accuracy |
| model-index: |
| - name: BERT-tiny-emotion-intent |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: emotion |
| type: emotion |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.91 |
| --- |
| |
| <!-- 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-tiny-emotion-intent |
|
|
| This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the emotion dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3620 |
| - Accuracy: 0.91 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 33 |
| - 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 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 1.2603 | 1.0 | 1000 | 0.7766 | 0.7815 | |
| | 0.5919 | 2.0 | 2000 | 0.4117 | 0.884 | |
| | 0.367 | 3.0 | 3000 | 0.3188 | 0.8995 | |
| | 0.2848 | 4.0 | 4000 | 0.2928 | 0.8985 | |
| | 0.2395 | 5.0 | 5000 | 0.2906 | 0.898 | |
| | 0.2094 | 6.0 | 6000 | 0.2887 | 0.907 | |
| | 0.1884 | 7.0 | 7000 | 0.2831 | 0.9065 | |
| | 0.1603 | 8.0 | 8000 | 0.3044 | 0.9065 | |
| | 0.1519 | 9.0 | 9000 | 0.3124 | 0.9095 | |
| | 0.1291 | 10.0 | 10000 | 0.3256 | 0.9065 | |
| | 0.1179 | 11.0 | 11000 | 0.3651 | 0.9035 | |
| | 0.1091 | 12.0 | 12000 | 0.3620 | 0.91 | |
| | 0.0977 | 13.0 | 13000 | 0.3992 | 0.907 | |
| | 0.0914 | 14.0 | 14000 | 0.4285 | 0.908 | |
| | 0.0876 | 15.0 | 15000 | 0.4268 | 0.9055 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.22.1 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.5.1 |
| - Tokenizers 0.12.1 |
|
|
