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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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- augmented_glue_sst2 |
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metrics: |
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- accuracy |
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model-index: |
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- name: miny-bert-aug-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: augmented_glue_sst2 |
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type: augmented_glue_sst2 |
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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: 0.9128440366972477 |
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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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# miny-bert-aug-sst2-distilled |
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This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the augmented_glue_sst2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2643 |
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- Accuracy: 0.9128 |
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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: 6e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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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| 0.602 | 1.0 | 6227 | 0.3389 | 0.9186 | |
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| 0.4195 | 2.0 | 12454 | 0.2989 | 0.9151 | |
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| 0.3644 | 3.0 | 18681 | 0.2794 | 0.9117 | |
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| 0.3304 | 4.0 | 24908 | 0.2793 | 0.9106 | |
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| 0.3066 | 5.0 | 31135 | 0.2659 | 0.9186 | |
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| 0.2881 | 6.0 | 37362 | 0.2668 | 0.9140 | |
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| 0.2754 | 7.0 | 43589 | 0.2643 | 0.9128 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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