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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: bert-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: Bert-RAdam-XL |
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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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# Bert-RAdam-XL |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1916 |
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- Precision: 0.8057 |
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- Recall: 0.8640 |
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- F1: 0.8338 |
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- Accuracy: 0.9455 |
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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: 0.0001 |
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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 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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.1843 | 1.0 | 1000 | 0.1410 | 0.7841 | 0.8672 | 0.8236 | 0.9436 | |
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| 0.1156 | 2.0 | 2000 | 0.1443 | 0.7981 | 0.8372 | 0.8172 | 0.9438 | |
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| 0.0862 | 3.0 | 3000 | 0.1562 | 0.7947 | 0.8961 | 0.8424 | 0.9477 | |
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| 0.0612 | 4.0 | 4000 | 0.1735 | 0.7976 | 0.8853 | 0.8392 | 0.9470 | |
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| 0.038 | 5.0 | 5000 | 0.1916 | 0.8057 | 0.8640 | 0.8338 | 0.9455 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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