---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deberta-v3-small-Label_B-768-epochs-5
  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. -->

# deberta-v3-small-Label_B-768-epochs-5

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0703
- Accuracy: 0.9868
- F1: 0.9868
- Precision: 0.9869
- Recall: 0.9868

## 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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0851        | 0.9995 | 1066 | 0.0843          | 0.9747   | 0.9746 | 0.9752    | 0.9747 |
| 0.0433        | 2.0    | 2133 | 0.0894          | 0.9755   | 0.9755 | 0.9764    | 0.9755 |
| 0.0251        | 2.9995 | 3199 | 0.0651          | 0.9829   | 0.9829 | 0.9831    | 0.9829 |
| 0.0025        | 4.0    | 4266 | 0.0703          | 0.9868   | 0.9868 | 0.9869    | 0.9868 |
| 0.0035        | 4.9977 | 5330 | 0.0996          | 0.9819   | 0.9820 | 0.9824    | 0.9819 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0