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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-distilBERT |
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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: 0.913 |
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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-distilBERT |
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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: 0.5444 |
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- Accuracy: 0.913 |
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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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| 4.2533 | 1.0 | 1000 | 2.8358 | 0.7675 | |
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| 2.3274 | 2.0 | 2000 | 1.5893 | 0.8675 | |
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| 1.3974 | 3.0 | 3000 | 1.0286 | 0.891 | |
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| 0.9035 | 4.0 | 4000 | 0.7534 | 0.8955 | |
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| 0.6619 | 5.0 | 5000 | 0.6350 | 0.905 | |
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| 0.5482 | 6.0 | 6000 | 0.6180 | 0.899 | |
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| 0.4937 | 7.0 | 7000 | 0.5448 | 0.91 | |
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| 0.4013 | 8.0 | 8000 | 0.5493 | 0.906 | |
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| 0.3839 | 9.0 | 9000 | 0.5481 | 0.9095 | |
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| 0.3281 | 10.0 | 10000 | 0.5528 | 0.9115 | |
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| 0.3098 | 11.0 | 11000 | 0.5864 | 0.9095 | |
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| 0.2762 | 12.0 | 12000 | 0.5566 | 0.9095 | |
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| 0.2467 | 13.0 | 13000 | 0.5444 | 0.913 | |
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| 0.2286 | 14.0 | 14000 | 0.5306 | 0.912 | |
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| 0.2215 | 15.0 | 15000 | 0.5312 | 0.9115 | |
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| 0.2038 | 16.0 | 16000 | 0.5242 | 0.912 | |
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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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