---
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deberta-v3-xsmall-Label_B-768-epochs-3
  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-xsmall-Label_B-768-epochs-3

This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1073
- Accuracy: 0.9741
- F1: 0.9741
- Precision: 0.9755
- Recall: 0.9741

## 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: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.12          | 0.9994 | 1279 | 0.2452          | 0.9352   | 0.9350 | 0.9420    | 0.9352 |
| 0.0496        | 1.9996 | 2559 | 0.1073          | 0.9741   | 0.9741 | 0.9755    | 0.9741 |
| 0.0294        | 2.9982 | 3837 | 0.1162          | 0.9739   | 0.9739 | 0.9751    | 0.9739 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.5.0+cu124
- Datasets 2.18.0
- Tokenizers 0.19.1