---
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-base-DIALOCONAN-WIKI-CLS
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deberta-base-DIALOCONAN-WIKI-CLS

This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3425
- Precision: 0.7075
- Recall: 0.7106
- F1: 0.7090
- Accuracy: 0.9442

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3743        | 1.0   | 2500 | 0.4070          | 0.6887    | 0.6918 | 0.6894 | 0.9183   |
| 0.2331        | 2.0   | 5000 | 0.3845          | 0.6980    | 0.7000 | 0.6989 | 0.9308   |
| 0.1176        | 3.0   | 7500 | 0.3425          | 0.7075    | 0.7106 | 0.7090 | 0.9442   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1