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# bio_gpt_ner

This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncbi_disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1558
- Precision: 0.8269
- Recall: 0.6463
- F1: 0.7255
- Accuracy: 0.9544

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3027        | 1.0   | 680  | 0.1893          | 0.8417    | 0.4194 | 0.5598 | 0.9405   |
| 0.2037        | 2.0   | 1360 | 0.1562          | 0.8082    | 0.6388 | 0.7136 | 0.9517   |
| 0.1228        | 3.0   | 2040 | 0.1558          | 0.8269    | 0.6463 | 0.7255 | 0.9544   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["ncbi_disease"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bio_gpt_ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "ncbi_disease", "type": "ncbi_disease", "config": "ncbi_disease", "split": "validation", "args": "ncbi_disease"}, "metrics": [{"type": "precision", "value": 0.826944757609921, "name": "Precision"}, {"type": "recall", "value": 0.6462555066079295, "name": "Recall"}, {"type": "f1", "value": 0.7255192878338279, "name": "F1"}, {"type": "accuracy", "value": 0.9543616855854455, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard gpt2 token-classification generated_from_trainer dataset:ncbi_disease license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #token-classification #generated_from_trainer #dataset-ncbi_disease #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

bio\_gpt\_ner
=============


This model is a fine-tuned version of microsoft/biogpt on the ncbi\_disease dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1558
* Precision: 0.8269
* Recall: 0.6463
* F1: 0.7255
* Accuracy: 0.9544


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: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #gpt2 #token-classification #generated_from_trainer #dataset-ncbi_disease #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #gpt2 #token-classification #generated_from_trainer #dataset-ncbi_disease #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3