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# SourceData_NER_v_1-0-2_BioLinkBERT_base

This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the source_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1320
- Accuracy Score: 0.9587
- Precision: 0.8320
- Recall: 0.8591
- F1: 0.8453

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
| 0.1227        | 1.0   | 471  | 0.1390          | 0.9547         | 0.7918    | 0.8745 | 0.8311 |
| 0.0852        | 2.0   | 942  | 0.1320          | 0.9587         | 0.8320    | 0.8591 | 0.8453 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0a0+bfe5ad2
- Datasets 2.10.1
- Tokenizers 0.12.1

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transformers pytorch bert token-classification generated_from_trainer dataset:source_data license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us