---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DIALOGUE_second_model
  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. -->

# DIALOGUE_second_model

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3364
- Precision: 0.9762
- Recall: 0.9737
- F1: 0.9736
- Accuracy: 0.9737

## 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: 1e-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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.3667        | 0.31  | 15   | 1.2505          | 0.2468    | 0.4868 | 0.3263 | 0.4868   |
| 1.1649        | 0.62  | 30   | 1.0587          | 0.8659    | 0.7105 | 0.6935 | 0.7105   |
| 1.0288        | 0.94  | 45   | 0.8905          | 0.9479    | 0.9342 | 0.9331 | 0.9342   |
| 0.8541        | 1.25  | 60   | 0.7069          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.6833        | 1.56  | 75   | 0.5616          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.6072        | 1.88  | 90   | 0.4586          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.4665        | 2.19  | 105  | 0.3944          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.4274        | 2.5   | 120  | 0.3563          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.4116        | 2.81  | 135  | 0.3364          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0