---
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: BBC_CLS_deberta_v3_large_v2
  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. -->

# BBC_CLS_deberta_v3_large_v2

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co./microsoft/deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0857
- Accuracy: 0.9866
- Precision: 0.9723
- Recall: 0.9780
- F1: 0.9751

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.235         | 1.0   | 66   | 0.6331          | 0.7964   | 0.4047    | 0.4873 | 0.4418 |
| 0.4336        | 2.0   | 132  | 0.2201          | 0.8971   | 0.6754    | 0.7091 | 0.6910 |
| 0.2133        | 3.0   | 198  | 0.0990          | 0.9776   | 0.9476    | 0.9786 | 0.9602 |
| 0.1083        | 4.0   | 264  | 0.1038          | 0.9821   | 0.9656    | 0.9651 | 0.9653 |
| 0.0848        | 5.0   | 330  | 0.0907          | 0.9866   | 0.9782    | 0.9714 | 0.9747 |
| 0.1087        | 6.0   | 396  | 0.1270          | 0.9799   | 0.9672    | 0.9689 | 0.9671 |
| 0.1011        | 7.0   | 462  | 0.1289          | 0.9754   | 0.9677    | 0.9660 | 0.9667 |
| 0.0827        | 8.0   | 528  | 0.0990          | 0.9799   | 0.9818    | 0.9479 | 0.9632 |
| 0.0621        | 9.0   | 594  | 0.0857          | 0.9866   | 0.9723    | 0.9780 | 0.9751 |
| 0.0444        | 10.0  | 660  | 0.1071          | 0.9843   | 0.9769    | 0.9663 | 0.9715 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 1.13.1
- Datasets 2.13.0
- Tokenizers 0.14.1