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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ag_news |
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metrics: |
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- accuracy |
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model-index: |
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- name: N_distilbert_agnews_padding100model |
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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: ag_news |
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type: ag_news |
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config: default |
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split: test |
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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: 0.9452631578947368 |
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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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# N_distilbert_agnews_padding100model |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ag_news dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6461 |
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- Accuracy: 0.9453 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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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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| 0.1812 | 1.0 | 7500 | 0.1853 | 0.9424 | |
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| 0.1417 | 2.0 | 15000 | 0.1940 | 0.9437 | |
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| 0.1201 | 3.0 | 22500 | 0.2239 | 0.9425 | |
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| 0.0895 | 4.0 | 30000 | 0.2896 | 0.9422 | |
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| 0.0604 | 5.0 | 37500 | 0.2957 | 0.9401 | |
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| 0.0471 | 6.0 | 45000 | 0.3845 | 0.9389 | |
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| 0.032 | 7.0 | 52500 | 0.4266 | 0.9393 | |
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| 0.0284 | 8.0 | 60000 | 0.4621 | 0.9420 | |
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| 0.0211 | 9.0 | 67500 | 0.4691 | 0.9384 | |
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| 0.0158 | 10.0 | 75000 | 0.4800 | 0.9417 | |
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| 0.0179 | 11.0 | 82500 | 0.5048 | 0.9422 | |
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| 0.0105 | 12.0 | 90000 | 0.4962 | 0.9453 | |
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| 0.0102 | 13.0 | 97500 | 0.5280 | 0.9437 | |
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| 0.0039 | 14.0 | 105000 | 0.5401 | 0.9442 | |
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| 0.0037 | 15.0 | 112500 | 0.5675 | 0.9441 | |
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| 0.0052 | 16.0 | 120000 | 0.5934 | 0.9454 | |
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| 0.003 | 17.0 | 127500 | 0.6308 | 0.9426 | |
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| 0.0014 | 18.0 | 135000 | 0.6194 | 0.9436 | |
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| 0.0007 | 19.0 | 142500 | 0.6454 | 0.945 | |
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| 0.0004 | 20.0 | 150000 | 0.6461 | 0.9453 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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