
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# MLMA_lab9

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: 0.3328
- Precision: 0.1239
- Recall: 0.0178
- F1: 0.0311
- Accuracy: 0.9177

## 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: 0.0001
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2903        | 1.0   | 680  | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.2907        | 2.0   | 1360 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.2885        | 3.0   | 2040 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.2861        | 4.0   | 2720 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.2948        | 5.0   | 3400 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.2881        | 6.0   | 4080 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.292         | 7.0   | 4760 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.2882        | 8.0   | 5440 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.2905        | 9.0   | 6120 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |
| 0.2881        | 10.0  | 6800 | 0.3328          | 0.1239    | 0.0178 | 0.0311 | 0.9177   |


### 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": "MLMA_lab9", "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": 0.12389380530973451, "name": "Precision"}, {"type": "recall", "value": 0.017789072426937738, "name": "Recall"}, {"type": "f1", "value": 0.031111111111111107, "name": "F1"}, {"type": "accuracy", "value": 0.9177455063979887, "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 

MLMA\_lab9
==========


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: 0.3328
* Precision: 0.1239
* Recall: 0.0178
* F1: 0.0311
* Accuracy: 0.9177


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: 0.0001
* 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: 10


### 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: 0.0001
* 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: 10 ### 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: 0.0001
* 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: 10 ### Training results ### Framework versions


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