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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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- f1 |
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model-index: |
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- name: distilbert-base-uncased-classifier |
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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-classifier |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2505 |
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- Accuracy: 0.8919 |
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- F1: 0.7899 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| No log | 0 | 0 | 0.6737 | 0.7493 | 0.0440 | |
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| No log | 0.2020 | 79 | 0.3465 | 0.8602 | 0.6820 | |
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| No log | 0.4041 | 158 | 0.3404 | 0.8458 | 0.7371 | |
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| No log | 0.6061 | 237 | 0.2951 | 0.8761 | 0.7650 | |
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| No log | 0.8082 | 316 | 0.2763 | 0.8862 | 0.7893 | |
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| No log | 1.0102 | 395 | 0.2732 | 0.8818 | 0.7747 | |
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| No log | 1.2123 | 474 | 0.2707 | 0.8905 | 0.7865 | |
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| 0.3426 | 1.4143 | 553 | 0.2516 | 0.8963 | 0.7989 | |
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| 0.3426 | 1.6164 | 632 | 0.2434 | 0.8963 | 0.7943 | |
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| 0.3426 | 1.8184 | 711 | 0.2505 | 0.8919 | 0.7899 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.7.0+cu126 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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