---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-finetuned-clinc_oos
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: clinc_oos
      type: clinc_oos
      config: plus
      split: test
      args: plus
    metrics:
    - name: Accuracy
      type: accuracy
      value:
        accuracy: 0.8672727272727273
    - name: F1
      type: f1
      value:
        f1: 0.8593551627139002
---

<!-- 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-finetuned-clinc_oos

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: 1.0863
- Accuracy: {'accuracy': 0.8672727272727273}
- F1: {'f1': 0.8593551627139002}

## Model Training Details

| Parameter            | Value                             |
|----------------------|-----------------------------------|
| **Task**             | text-classification               |
| **Base Model Name**  | bert-base-uncased                 |
| **Dataset Name**     | clinc_oos                         |
| **Dataset Config**   | plus                              |
| **Batch Size**       | 16                                |
| **Number of Epochs** | 3                                 |
| **Learning Rate**    | 0.00002                           |


## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1                         |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
| 4.3415        | 1.0   | 954  | 2.4724          | {'accuracy': 0.7769090909090909} | {'f1': 0.7596942777117995} |
| 1.7949        | 2.0   | 1908 | 1.3415          | {'accuracy': 0.8538181818181818} | {'f1': 0.8441232118060242} |
| 0.8898        | 3.0   | 2862 | 1.0863          | {'accuracy': 0.8672727272727273} | {'f1': 0.8593551627139002} |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3