---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: xlm-roberta-base
metrics:
- accuracy
- f1
model-index:
- name: prompt_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. -->

# prompt_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: 1.4733
- Accuracy: 0.3182
- F1: 0.1536

## 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: 1
- eval_batch_size: 1
- 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.9542        | 0.4545 | 50   | 1.1060          | 0.3182   | 0.1536 |
| 0.8627        | 0.9091 | 100  | 1.1621          | 0.3182   | 0.1536 |
| 0.6647        | 1.3636 | 150  | 1.2304          | 0.3182   | 0.1536 |
| 0.8065        | 1.8182 | 200  | 1.3215          | 0.3182   | 0.1536 |
| 0.7675        | 2.2727 | 250  | 1.3718          | 0.3182   | 0.1536 |
| 0.8203        | 2.7273 | 300  | 1.4238          | 0.3182   | 0.1536 |
| 0.7817        | 3.1818 | 350  | 1.4576          | 0.3182   | 0.1536 |
| 0.7012        | 3.6364 | 400  | 1.4733          | 0.3182   | 0.1536 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1