---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine-tuned-NLI-multilingual-with-xlm-roberta-large
  results: []
---

<!-- 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. -->

# fine-tuned-NLI-multilingual-with-xlm-roberta-large

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4158
- Accuracy: 0.8600
- F1: 0.8612

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Accuracy | F1     | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|
| 0.4647        | 0.5   | 1613  | 0.8396   | 0.8403 | 0.4262          |
| 0.4437        | 1.0   | 3226  | 0.8511   | 0.8522 | 0.4042          |
| 0.3956        | 1.5   | 4839  | 0.3783   | 0.8604 | 0.8602          |
| 0.3639        | 2.0   | 6452  | 0.3913   | 0.8592 | 0.8600          |
| 0.323         | 2.5   | 8065  | 0.3783   | 0.8657 | 0.8659          |
| 0.3186        | 3.0   | 9678  | 0.3850   | 0.8626 | 0.8625          |
| 0.2485        | 3.5   | 11291 | 0.4326   | 0.8597 | 0.8592          |
| 0.2509        | 4.0   | 12904 | 0.4158   | 0.8600 | 0.8612          |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.3