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--- |
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library_name: transformers |
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license: mit |
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base_model: roberta-base |
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tags: |
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- bert-ner-address-1 |
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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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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0207 |
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- Precision: 0.9947 |
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- Recall: 0.9949 |
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- F1: 0.9948 |
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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: 5e-05 |
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- train_batch_size: 32 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | |
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|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:| |
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| 0.0274 | 1.0 | 35645 | 0.0271 | 0.9881 | 0.9915 | 0.9898 | |
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| 0.0424 | 2.0 | 71290 | 0.0244 | 0.9935 | 0.9941 | 0.9938 | |
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| 0.0162 | 3.0 | 106935 | 0.0218 | 0.9945 | 0.9947 | 0.9946 | |
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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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