
<!-- 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. -->

# zero-shot_text_classification_2

This model is a fine-tuned version of [MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli](https://huggingface.co/MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7107
- Accuracy: 0.77
- F1: 0.7697

## 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-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9528        | 1.0   | 1000 | 0.7107          | 0.77     | 0.7697 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli", "model-index": [{"name": "zero-shot_text_classification_2", "results": []}]}
transformers tensorboard safetensors deberta-v2 text-classification generated_from_trainer base_model:MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli license:mit autotrain_compatible endpoints_compatible region:us