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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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- glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: tiny-bert-sst2-distilled |
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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: glue |
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type: glue |
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args: sst2 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8325688073394495 |
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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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# tiny-bert-sst2-distilled |
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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 glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7305 |
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- Accuracy: 0.8326 |
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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: 0.0007199555649276667 |
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- train_batch_size: 1024 |
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- eval_batch_size: 1024 |
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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: 7 |
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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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| 1.77 | 1.0 | 66 | 1.6939 | 0.8165 | |
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| 0.729 | 2.0 | 132 | 1.5090 | 0.8326 | |
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| 0.5242 | 3.0 | 198 | 1.5369 | 0.8257 | |
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| 0.4017 | 4.0 | 264 | 1.7025 | 0.8326 | |
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| 0.327 | 5.0 | 330 | 1.6743 | 0.8245 | |
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| 0.2749 | 6.0 | 396 | 1.7305 | 0.8337 | |
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| 0.2521 | 7.0 | 462 | 1.7305 | 0.8326 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.9.1 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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