transformers tensorboard safetensors bert token-classification generated_from_trainer base_model:dmis-lab/biobert-v1.1 base_model:finetune:dmis-lab/biobert-v1.1 autotrain_compatible endpoints_compatible region:us
---
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_trainer
model-index:
- name: CRAFT_bioBERT_NER
  results: []
---

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# CRAFT_bioBERT_NER

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1106
- Seqeval classification report:               precision    recall  f1-score   support

       CHEBI       0.83      0.76      0.80      1109
          CL       0.91      0.90      0.90      3871
         GGP       0.76      0.66      0.71       600
          GO       0.87      0.84      0.85      1061
          SO       0.99      0.99      0.99     87954
       Taxon       0.83      0.87      0.85      3104

   micro avg       0.98      0.97      0.97     97699
   macro avg       0.87      0.84      0.85     97699
weighted avg       0.98      0.97      0.97     97699


## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Seqeval classification report                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| No log        | 1.0   | 347  | 0.1141          |               precision    recall  f1-score   support

       CHEBI       0.82      0.65      0.72      1109
          CL       0.90      0.87      0.89      3871
         GGP       0.75      0.62      0.68       600
          GO       0.88      0.77      0.82      1061
          SO       0.99      0.99      0.99     87954
       Taxon       0.79      0.88      0.83      3104

   micro avg       0.97      0.97      0.97     97699
   macro avg       0.86      0.80      0.82     97699
weighted avg       0.97      0.97      0.97     97699
 |
| 0.1705        | 2.0   | 695  | 0.1121          |               precision    recall  f1-score   support

       CHEBI       0.86      0.73      0.79      1109
          CL       0.90      0.90      0.90      3871
         GGP       0.73      0.65      0.69       600
          GO       0.87      0.82      0.85      1061
          SO       0.99      0.99      0.99     87954
       Taxon       0.79      0.89      0.84      3104

   micro avg       0.97      0.97      0.97     97699
   macro avg       0.86      0.83      0.84     97699
weighted avg       0.97      0.97      0.97     97699
 |
| 0.04          | 3.0   | 1041 | 0.1106          |               precision    recall  f1-score   support

       CHEBI       0.83      0.76      0.80      1109
          CL       0.91      0.90      0.90      3871
         GGP       0.76      0.66      0.71       600
          GO       0.87      0.84      0.85      1061
          SO       0.99      0.99      0.99     87954
       Taxon       0.83      0.87      0.85      3104

   micro avg       0.98      0.97      0.97     97699
   macro avg       0.87      0.84      0.85     97699
weighted avg       0.98      0.97      0.97     97699
 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
