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# bert-finetuned-ncbi

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the ncbi_disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0679
- Precision: 0.7807
- Recall: 0.8640
- F1: 0.8203
- Accuracy: 0.9831

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1146        | 1.0   | 680  | 0.0686          | 0.7450    | 0.8056 | 0.7741 | 0.9805   |
| 0.0458        | 2.0   | 1360 | 0.0612          | 0.7646    | 0.8628 | 0.8107 | 0.9815   |
| 0.0161        | 3.0   | 2040 | 0.0679          | 0.7807    | 0.8640 | 0.8203 | 0.9831   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["ncbi_disease"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-finetuned-ncbi", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "ncbi_disease", "type": "ncbi_disease", "config": "ncbi_disease", "split": "train", "args": "ncbi_disease"}, "metrics": [{"type": "precision", "value": 0.7807118254879449, "name": "Precision"}, {"type": "recall", "value": 0.8640406607369758, "name": "Recall"}, {"type": "f1", "value": 0.8202653799758745, "name": "F1"}, {"type": "accuracy", "value": 0.9831009585459978, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer dataset:ncbi_disease license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-ncbi_disease #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-finetuned-ncbi
===================


This model is a fine-tuned version of bert-base-cased on the ncbi\_disease dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0679
* Precision: 0.7807
* Recall: 0.8640
* F1: 0.8203
* Accuracy: 0.9831


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: 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 4.25.1
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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 4.25.1
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-ncbi_disease #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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 4.25.1
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-ncbi_disease #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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 4.25.1
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.13.2