---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta-v3-base-finetuned-emo_une
  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-base-finetuned-emo_une

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4500
- Accuracy: 0.865
- F1: 0.8681

## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.68          | 1.0   | 26   | 0.6269          | 0.585    | 0.6107 |
| 0.5312        | 2.0   | 52   | 0.4552          | 0.86     | 0.8578 |
| 0.3854        | 3.0   | 78   | 0.4478          | 0.84     | 0.8441 |
| 0.3005        | 4.0   | 104  | 0.4395          | 0.86     | 0.8644 |
| 0.258         | 5.0   | 130  | 0.4500          | 0.865    | 0.8681 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1