---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DIALOGUE_two
  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_two

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3804
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.3711        | 0.31  | 15   | 1.3213          | 0.5848    | 0.5132 | 0.4588 | 0.5132   |
| 1.2829        | 0.62  | 30   | 1.1830          | 0.7679    | 0.7237 | 0.7027 | 0.7237   |
| 1.1039        | 0.94  | 45   | 0.9695          | 0.8939    | 0.8158 | 0.8094 | 0.8158   |
| 0.9122        | 1.25  | 60   | 0.7720          | 0.9499    | 0.9474 | 0.9473 | 0.9474   |
| 0.7581        | 1.56  | 75   | 0.6220          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.6483        | 1.88  | 90   | 0.5096          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.5277        | 2.19  | 105  | 0.4330          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.4708        | 2.5   | 120  | 0.4003          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |
| 0.4622        | 2.81  | 135  | 0.3804          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1