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--- |
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library_name: transformers |
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license: mit |
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base_model: BAAI/bge-small-en-v1.5 |
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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-finetuned-ner |
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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-finetuned-ner |
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This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0881 |
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- Precision: 0.8860 |
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- Recall: 0.9197 |
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- F1: 0.9026 |
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- Accuracy: 0.9801 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 3 |
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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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| 0.0671 | 1.0 | 1250 | 0.0929 | 0.8681 | 0.9150 | 0.8909 | 0.9774 | |
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| 0.0428 | 2.0 | 2500 | 0.0871 | 0.8909 | 0.9177 | 0.9041 | 0.9800 | |
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| 0.0373 | 3.0 | 3750 | 0.0881 | 0.8860 | 0.9197 | 0.9026 | 0.9801 | |
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### Framework versions |
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- Transformers 4.50.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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