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--- |
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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 [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6434 |
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- Precision: 0.8589 |
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- Recall: 0.8686 |
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- F1: 0.8637 |
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- Accuracy: 0.8324 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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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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| 0.615 | 1.0 | 1741 | 0.6111 | 0.8200 | 0.8652 | 0.8420 | 0.8046 | |
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| 0.4795 | 2.0 | 3482 | 0.5366 | 0.8456 | 0.8803 | 0.8626 | 0.8301 | |
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| 0.3705 | 3.0 | 5223 | 0.5412 | 0.8527 | 0.8786 | 0.8655 | 0.8339 | |
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| 0.2749 | 4.0 | 6964 | 0.5906 | 0.8559 | 0.8711 | 0.8634 | 0.8316 | |
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| 0.2049 | 5.0 | 8705 | 0.6434 | 0.8589 | 0.8686 | 0.8637 | 0.8324 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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