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

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: 1.1527
- Precision: 0.8207
- Recall: 0.8158
- F1: 0.8103
- Accuracy: 0.8158

## 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: 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.3373        | 0.62  | 30   | 1.2236          | 0.6642    | 0.5263 | 0.4857 | 0.5263   |
| 0.9036        | 1.25  | 60   | 0.8198          | 0.7325    | 0.7237 | 0.7209 | 0.7237   |
| 0.5825        | 1.88  | 90   | 0.6795          | 0.7291    | 0.7237 | 0.7257 | 0.7237   |
| 0.4134        | 2.5   | 120  | 0.5864          | 0.8026    | 0.8026 | 0.8017 | 0.8026   |
| 0.2866        | 3.12  | 150  | 0.6642          | 0.7360    | 0.7368 | 0.7352 | 0.7368   |
| 0.2291        | 3.75  | 180  | 0.7632          | 0.7673    | 0.7632 | 0.7646 | 0.7632   |
| 0.2907        | 4.38  | 210  | 0.7228          | 0.8109    | 0.7632 | 0.7607 | 0.7632   |
| 0.1721        | 5.0   | 240  | 0.7910          | 0.7793    | 0.7763 | 0.7765 | 0.7763   |
| 0.1475        | 5.62  | 270  | 0.7622          | 0.8173    | 0.8158 | 0.8156 | 0.8158   |
| 0.1541        | 6.25  | 300  | 0.6803          | 0.7911    | 0.7895 | 0.7896 | 0.7895   |
| 0.0706        | 6.88  | 330  | 0.8729          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0825        | 7.5   | 360  | 0.8173          | 0.8472    | 0.8421 | 0.8408 | 0.8421   |
| 0.0419        | 8.12  | 390  | 0.6985          | 0.8356    | 0.8289 | 0.8294 | 0.8289   |
| 0.0588        | 8.75  | 420  | 0.7242          | 0.8137    | 0.8026 | 0.8041 | 0.8026   |
| 0.0535        | 9.38  | 450  | 0.9187          | 0.8060    | 0.8026 | 0.8007 | 0.8026   |
| 0.0275        | 10.0  | 480  | 1.3225          | 0.7839    | 0.7763 | 0.7615 | 0.7763   |
| 0.01          | 10.62 | 510  | 1.2285          | 0.7667    | 0.7632 | 0.7533 | 0.7632   |
| 0.0336        | 11.25 | 540  | 1.1652          | 0.8170    | 0.8026 | 0.7976 | 0.8026   |
| 0.0031        | 11.88 | 570  | 0.8795          | 0.7941    | 0.7895 | 0.7854 | 0.7895   |
| 0.0019        | 12.5  | 600  | 1.0385          | 0.8076    | 0.8026 | 0.7971 | 0.8026   |
| 0.0035        | 13.12 | 630  | 1.1230          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0016        | 13.75 | 660  | 1.0793          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0014        | 14.38 | 690  | 1.0877          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0015        | 15.0  | 720  | 1.1482          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0012        | 15.62 | 750  | 1.1424          | 0.7935    | 0.7895 | 0.7834 | 0.7895   |
| 0.0011        | 16.25 | 780  | 1.0405          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0011        | 16.88 | 810  | 1.4101          | 0.7874    | 0.7763 | 0.7630 | 0.7763   |
| 0.0012        | 17.5  | 840  | 1.2321          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.001         | 18.12 | 870  | 1.1961          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.001         | 18.75 | 900  | 1.1638          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0009        | 19.38 | 930  | 1.1429          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0009        | 20.0  | 960  | 1.3692          | 0.7839    | 0.7763 | 0.7615 | 0.7763   |
| 0.0009        | 20.62 | 990  | 1.3196          | 0.7839    | 0.7763 | 0.7615 | 0.7763   |
| 0.0008        | 21.25 | 1020 | 1.1942          | 0.7839    | 0.7763 | 0.7615 | 0.7763   |
| 0.0008        | 21.88 | 1050 | 1.1439          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0008        | 22.5  | 1080 | 1.1689          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0008        | 23.12 | 1110 | 1.1553          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0007        | 23.75 | 1140 | 1.1560          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0007        | 24.38 | 1170 | 1.1451          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0007        | 25.0  | 1200 | 1.1473          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0007        | 25.62 | 1230 | 1.1412          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0007        | 26.25 | 1260 | 1.1655          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0007        | 26.88 | 1290 | 1.1649          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0006        | 27.5  | 1320 | 1.1556          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0006        | 28.12 | 1350 | 1.1521          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0006        | 28.75 | 1380 | 1.1481          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0008        | 29.38 | 1410 | 1.1511          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |
| 0.0006        | 30.0  | 1440 | 1.1527          | 0.8207    | 0.8158 | 0.8103 | 0.8158   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0