---
library_name: transformers
license: mit
base_model: PracticalWork/xlm-roberta-large-classifier
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-large-classifier-classifier-prompted
  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. -->

# xlm-roberta-large-classifier-classifier-prompted

This model is a fine-tuned version of [PracticalWork/xlm-roberta-large-classifier](https://huggingface.co/PracticalWork/xlm-roberta-large-classifier) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3406
- Accuracy: 0.8891
- F1: 0.8898

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 0     | 0    | 0.8239          | 0.7029   | 0.6341 |
| No log        | 0.6   | 255  | 0.3202          | 0.8832   | 0.8681 |
| 0.3462        | 1.2   | 510  | 0.2943          | 0.8827   | 0.8824 |
| 0.3462        | 1.8   | 765  | 0.2771          | 0.8967   | 0.8942 |
| 0.2258        | 2.4   | 1020 | 0.3878          | 0.8768   | 0.8796 |
| 0.2258        | 3.0   | 1275 | 0.3406          | 0.8891   | 0.8898 |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1