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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- emotion |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert-tiny-emotion-KD-BERT |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: emotion |
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type: emotion |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9175 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-tiny-emotion-KD-BERT |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4810 |
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- Accuracy: 0.9175 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 33 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 3.8247 | 1.0 | 1000 | 2.5170 | 0.7745 | |
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| 1.9864 | 2.0 | 2000 | 1.3436 | 0.874 | |
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| 1.1126 | 3.0 | 3000 | 0.8299 | 0.894 | |
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| 0.6924 | 4.0 | 4000 | 0.6500 | 0.9025 | |
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| 0.5272 | 5.0 | 5000 | 0.6097 | 0.908 | |
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| 0.4298 | 6.0 | 6000 | 0.5913 | 0.904 | |
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| 0.3936 | 7.0 | 7000 | 0.5165 | 0.9135 | |
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| 0.3238 | 8.0 | 8000 | 0.5120 | 0.9075 | |
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| 0.3018 | 9.0 | 9000 | 0.4989 | 0.916 | |
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| 0.2605 | 10.0 | 10000 | 0.4810 | 0.9175 | |
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| 0.2512 | 11.0 | 11000 | 0.4757 | 0.9135 | |
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| 0.219 | 12.0 | 12000 | 0.4676 | 0.914 | |
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| 0.2046 | 13.0 | 13000 | 0.4794 | 0.911 | |
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### Framework versions |
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- Transformers 4.22.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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