---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ts_tg
  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. -->

# ts_tg

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0516
- Accuracy: 0.8517
- F1: 0.8759
- Precision: 0.8996
- Recall: 0.8533

## 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: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 202  | 0.1370          | 0.5242   | 0.6378 | 0.8129    | 0.5248 |
| No log        | 2.0   | 404  | 0.0857          | 0.6877   | 0.7700 | 0.8749    | 0.6875 |
| 0.1567        | 3.0   | 606  | 0.0667          | 0.7810   | 0.8331 | 0.8929    | 0.7809 |
| 0.1567        | 4.0   | 808  | 0.0593          | 0.8145   | 0.8525 | 0.8947    | 0.8142 |
| 0.0566        | 5.0   | 1010 | 0.0554          | 0.8406   | 0.8668 | 0.8926    | 0.8425 |
| 0.0566        | 6.0   | 1212 | 0.0529          | 0.8437   | 0.8718 | 0.8994    | 0.8459 |
| 0.0566        | 7.0   | 1414 | 0.0522          | 0.8474   | 0.8737 | 0.8992    | 0.8496 |
| 0.0383        | 8.0   | 1616 | 0.0516          | 0.8517   | 0.8759 | 0.8996    | 0.8533 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1