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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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metrics: |
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- accuracy |
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model-index: |
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- name: distilbert-base-uncased__sst2__train-32-7 |
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results: [] |
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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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# distilbert-base-uncased__sst2__train-32-7 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6736 |
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- Accuracy: 0.5931 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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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| 0.7094 | 1.0 | 13 | 0.6887 | 0.5385 | |
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| 0.651 | 2.0 | 26 | 0.6682 | 0.6923 | |
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| 0.6084 | 3.0 | 39 | 0.6412 | 0.6923 | |
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| 0.4547 | 4.0 | 52 | 0.6095 | 0.6923 | |
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| 0.2903 | 5.0 | 65 | 0.6621 | 0.6923 | |
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| 0.1407 | 6.0 | 78 | 0.7130 | 0.7692 | |
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| 0.0444 | 7.0 | 91 | 0.9007 | 0.6923 | |
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| 0.0176 | 8.0 | 104 | 0.9525 | 0.7692 | |
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| 0.0098 | 9.0 | 117 | 1.0289 | 0.7692 | |
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| 0.0071 | 10.0 | 130 | 1.0876 | 0.7692 | |
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| 0.0052 | 11.0 | 143 | 1.1431 | 0.6923 | |
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| 0.0038 | 12.0 | 156 | 1.1687 | 0.7692 | |
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| 0.0034 | 13.0 | 169 | 1.1792 | 0.7692 | |
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| 0.0031 | 14.0 | 182 | 1.2033 | 0.7692 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2 |
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- Tokenizers 0.10.3 |
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