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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- source_data |
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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-large-cased-lora-finetuned-ner-EMBO-SourceData |
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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-large-cased-lora-finetuned-ner-EMBO-SourceData |
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This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the source_data dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1282 |
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- Precision: 0.7999 |
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- Recall: 0.8278 |
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- F1: 0.8136 |
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- Accuracy: 0.9584 |
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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: 0.001 |
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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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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| 0.1552 | 1.0 | 3454 | 0.1499 | 0.7569 | 0.7968 | 0.7763 | 0.9516 | |
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| 0.1179 | 2.0 | 6908 | 0.1328 | 0.7910 | 0.8120 | 0.8013 | 0.9564 | |
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| 0.0998 | 3.0 | 10362 | 0.1282 | 0.7999 | 0.8278 | 0.8136 | 0.9584 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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