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# electramed-small-NCBI-ner

This model is a fine-tuned version of [giacomomiolo/electramed_small_scivocab](https://huggingface.co/giacomomiolo/electramed_small_scivocab) on the ncbi_disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0664
- Precision: 0.8083
- Recall: 0.8875
- F1: 0.8461
- Accuracy: 0.9821

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4787        | 1.0   | 340  | 0.5090          | 0.6090    | 0.5062 | 0.5529 | 0.9608   |
| 0.2029        | 2.0   | 680  | 0.1890          | 0.7643    | 0.8208 | 0.7916 | 0.9774   |
| 0.1402        | 3.0   | 1020 | 0.1106          | 0.7839    | 0.8802 | 0.8292 | 0.9807   |
| 0.075         | 4.0   | 1360 | 0.0876          | 0.8162    | 0.8698 | 0.8422 | 0.9817   |
| 0.0408        | 5.0   | 1700 | 0.0776          | 0.8090    | 0.8781 | 0.8422 | 0.9818   |
| 0.0308        | 6.0   | 2040 | 0.0697          | 0.8044    | 0.8823 | 0.8415 | 0.9825   |
| 0.0405        | 7.0   | 2380 | 0.0680          | 0.8118    | 0.8854 | 0.8470 | 0.9830   |
| 0.0138        | 8.0   | 2720 | 0.0665          | 0.8111    | 0.8854 | 0.8466 | 0.9826   |
| 0.0223        | 9.0   | 3060 | 0.0675          | 0.8064    | 0.8896 | 0.8460 | 0.9821   |
| 0.0395        | 10.0  | 3400 | 0.0664          | 0.8083    | 0.8875 | 0.8461 | 0.9821   |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["ncbi_disease"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "electramed-small-NCBI-ner", "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": 0.8083491461100569, "name": "Precision"}, {"type": "recall", "value": 0.8875, "name": "Recall"}, {"type": "f1", "value": 0.846077457795432, "name": "F1"}, {"type": "accuracy", "value": 0.9820794382985671, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard electra token-classification generated_from_trainer dataset:ncbi_disease model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #electra #token-classification #generated_from_trainer #dataset-ncbi_disease #model-index #autotrain_compatible #endpoints_compatible #region-us 

electramed-small-NCBI-ner
=========================


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


* Loss: 0.0664
* Precision: 0.8083
* Recall: 0.8875
* F1: 0.8461
* Accuracy: 0.9821


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
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #electra #token-classification #generated_from_trainer #dataset-ncbi_disease #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #electra #token-classification #generated_from_trainer #dataset-ncbi_disease #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1