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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-uncased |
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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-finetuning |
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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-finetuning |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co./distilbert/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: 0.4057 |
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- Accuracy: 0.8387 |
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- F1 Macro: 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: 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| 0.7293 | 1.0 | 907 | 0.4495 | 0.8206 | 0.8107 | |
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| 0.377 | 2.0 | 1814 | 0.3867 | 0.8422 | 0.8389 | |
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| 0.2841 | 3.0 | 2721 | 0.4231 | 0.8383 | 0.8324 | |
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| 0.1976 | 4.0 | 3628 | 0.4991 | 0.8366 | 0.8304 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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