pytorch tensorboard bert text-classification dataset:clinc_oos transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
model-index:
- name: bert-base-uncased-fine-tuned-on-clinc_oos-dataset
  results: []
---

<!-- 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. -->

# bert-base-uncased-fine-tuned-on-clinc_oos-dataset

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the clinc_oos dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2811
- Accuracy Score: 0.9239
- F1 Score: 0.9213

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:--------:|
| 4.4271        | 1.0   | 239  | 3.5773          | 0.6116         | 0.5732   |
| 3.0415        | 2.0   | 478  | 2.4076          | 0.8390         | 0.8241   |
| 2.1182        | 3.0   | 717  | 1.7324          | 0.8994         | 0.8934   |
| 1.5897        | 4.0   | 956  | 1.3863          | 0.9210         | 0.9171   |
| 1.3458        | 5.0   | 1195 | 1.2811          | 0.9239         | 0.9213   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
