---
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: 0.3866
- Precision: 0.6323
- Recall: 0.6344
- F1: 0.6333
- Accuracy: 0.9484

## 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3835        | 1.0   | 2500  | 0.4185          | 0.6829    | 0.6859 | 0.6832 | 0.9097   |
| 0.2718        | 2.0   | 5000  | 0.3822          | 0.7011    | 0.7016 | 0.7011 | 0.9329   |
| 0.1602        | 3.0   | 7500  | 0.3330          | 0.6302    | 0.6321 | 0.6311 | 0.9451   |
| 0.1018        | 4.0   | 10000 | 0.3639          | 0.6332    | 0.6351 | 0.6340 | 0.9496   |
| 0.0508        | 5.0   | 12500 | 0.3866          | 0.6323    | 0.6344 | 0.6333 | 0.9484   |


### Framework versions

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