---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_cb_XLMroberta
  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_cb_XLMroberta

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4876
- Accuracy: 0.6364
- F1: 0.5977

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.8279        | 3.5714  | 50   | 1.1428          | 0.3182   | 0.1536 |
| 0.6981        | 7.1429  | 100  | 1.2578          | 0.3182   | 0.1536 |
| 0.6005        | 10.7143 | 150  | 1.2018          | 0.3636   | 0.2430 |
| 0.2959        | 14.2857 | 200  | 1.1990          | 0.6364   | 0.5916 |
| 0.1743        | 17.8571 | 250  | 1.5253          | 0.5909   | 0.5562 |
| 0.1206        | 21.4286 | 300  | 1.8099          | 0.5      | 0.4423 |
| 0.0357        | 25.0    | 350  | 1.7105          | 0.5909   | 0.5545 |
| 0.0189        | 28.5714 | 400  | 1.4876          | 0.6364   | 0.5977 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1