---
library_name: transformers
license: mit
base_model: microsoft/deberta-v2-xlarge-mnli
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ms-deberta-v2-xlarge-mnli-finetuned-pt
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ms-deberta-v2-xlarge-mnli-finetuned-pt

This model is a fine-tuned version of [microsoft/deberta-v2-xlarge-mnli](https://huggingface.co/microsoft/deberta-v2-xlarge-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7274
- Accuracy: 0.8571
- Precision: 0.4286
- Recall: 0.5
- F1: 0.4615
- Ratio: 0.0

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- lr_scheduler_warmup_steps: 4
- num_epochs: 3
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----:|
| 0.8996        | 1.5385 | 10   | 0.6120          | 0.8571   | 0.4286    | 0.5    | 0.4615 | 0.0   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1