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# Originalbiobert-v1.1-BioRED-CD-128-32-30

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Precision: 0.9994
- Recall: 1.0
- F1: 0.9997

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0

### Training results



### Framework versions

- Transformers 4.11.3
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1"], "model-index": [{"name": "Originalbiobert-v1.1-BioRED-CD-128-32-30", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# Originalbiobert-v1.1-BioRED-CD-128-32-30

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Precision: 0.9994
- Recall: 1.0
- F1: 0.9997

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0

### Training results



### Framework versions

- Transformers 4.11.3
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.10.3

# Originalbiobert-v1.1-BioRED-CD-128-32-30

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Precision: 0.9994
- Recall: 1.0
- F1: 0.9997 ## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0 ### Training results ### Framework versions

- Transformers 4.11.3
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # Originalbiobert-v1.1-BioRED-CD-128-32-30

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Precision: 0.9994
- Recall: 1.0
- F1: 0.9997 ## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0 ### Training results ### Framework versions

- Transformers 4.11.3
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# Originalbiobert-v1.1-BioRED-CD-128-32-30

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Precision: 0.9994
- Recall: 1.0
- F1: 0.9997## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0### Training results### Framework versions

- Transformers 4.11.3
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.10.3