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

This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2989
- Accuracy: 0.9062
- F1: 0.9333

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 180  | 0.3227          | 0.8781   | 0.9150 |
| No log        | 2.0   | 360  | 0.3293          | 0.8562   | 0.8940 |
| 0.3756        | 3.0   | 540  | 0.3180          | 0.8906   | 0.9210 |
| 0.3756        | 4.0   | 720  | 0.2866          | 0.9094   | 0.9357 |
| 0.3756        | 5.0   | 900  | 0.2989          | 0.9062   | 0.9333 |


### Framework versions

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