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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-8-6 |
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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-8-6 |
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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: 0.5336 |
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- Accuracy: 0.7523 |
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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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| 0.7161 | 1.0 | 3 | 0.6941 | 0.5 | |
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| 0.6786 | 2.0 | 6 | 0.7039 | 0.25 | |
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| 0.6586 | 3.0 | 9 | 0.7090 | 0.25 | |
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| 0.6121 | 4.0 | 12 | 0.7183 | 0.25 | |
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| 0.5696 | 5.0 | 15 | 0.7266 | 0.25 | |
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| 0.522 | 6.0 | 18 | 0.7305 | 0.25 | |
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| 0.4899 | 7.0 | 21 | 0.7339 | 0.25 | |
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| 0.3985 | 8.0 | 24 | 0.7429 | 0.25 | |
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| 0.3758 | 9.0 | 27 | 0.7224 | 0.25 | |
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| 0.2876 | 10.0 | 30 | 0.7068 | 0.5 | |
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| 0.2498 | 11.0 | 33 | 0.6751 | 0.75 | |
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| 0.1921 | 12.0 | 36 | 0.6487 | 0.75 | |
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| 0.1491 | 13.0 | 39 | 0.6261 | 0.75 | |
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| 0.1276 | 14.0 | 42 | 0.6102 | 0.75 | |
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| 0.0996 | 15.0 | 45 | 0.5964 | 0.75 | |
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| 0.073 | 16.0 | 48 | 0.6019 | 0.75 | |
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| 0.0627 | 17.0 | 51 | 0.5933 | 0.75 | |
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| 0.053 | 18.0 | 54 | 0.5768 | 0.75 | |
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| 0.0403 | 19.0 | 57 | 0.5698 | 0.75 | |
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| 0.0328 | 20.0 | 60 | 0.5656 | 0.75 | |
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| 0.03 | 21.0 | 63 | 0.5634 | 0.75 | |
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| 0.025 | 22.0 | 66 | 0.5620 | 0.75 | |
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| 0.0209 | 23.0 | 69 | 0.5623 | 0.75 | |
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| 0.0214 | 24.0 | 72 | 0.5606 | 0.75 | |
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| 0.0191 | 25.0 | 75 | 0.5565 | 0.75 | |
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| 0.0173 | 26.0 | 78 | 0.5485 | 0.75 | |
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| 0.0175 | 27.0 | 81 | 0.5397 | 0.75 | |
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| 0.0132 | 28.0 | 84 | 0.5322 | 0.75 | |
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| 0.0138 | 29.0 | 87 | 0.5241 | 0.75 | |
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| 0.0128 | 30.0 | 90 | 0.5235 | 0.75 | |
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| 0.0126 | 31.0 | 93 | 0.5253 | 0.75 | |
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| 0.012 | 32.0 | 96 | 0.5317 | 0.75 | |
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| 0.0118 | 33.0 | 99 | 0.5342 | 0.75 | |
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| 0.0092 | 34.0 | 102 | 0.5388 | 0.75 | |
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| 0.0117 | 35.0 | 105 | 0.5414 | 0.75 | |
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| 0.0124 | 36.0 | 108 | 0.5453 | 0.75 | |
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| 0.0109 | 37.0 | 111 | 0.5506 | 0.75 | |
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| 0.0112 | 38.0 | 114 | 0.5555 | 0.75 | |
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| 0.0087 | 39.0 | 117 | 0.5597 | 0.75 | |
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| 0.01 | 40.0 | 120 | 0.5640 | 0.75 | |
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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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