---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: deberta-v3-base-finetuned-coling24
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deberta-v3-base-finetuned-coling24

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4024
- Accuracy: 0.7172
- F1: 0.6969

## 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: 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2662        | 1.0   | 1909 | 0.9077          | 0.7468   | 0.7402 |
| 0.134         | 2.0   | 3818 | 1.4337          | 0.7099   | 0.6963 |
| 0.0734        | 3.0   | 5727 | 1.6688          | 0.6912   | 0.6617 |
| 0.037         | 4.0   | 7636 | 2.1374          | 0.7199   | 0.7047 |
| 0.017         | 5.0   | 9545 | 2.4024          | 0.7172   | 0.6969 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1