---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlmr-stl-base-sentiment
  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. -->

# xlmr-stl-base-sentiment

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7501
- Sentiment Precision: 0.7167
- Sentiment Recall: 0.7172
- F1: 0.7158
- Sentiment Acc: 0.7219

## 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: 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: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Sentiment Precision | Sentiment Recall | F1     | Sentiment Acc |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------:|:-------------:|
| 0.8405        | 1.0   | 402  | 0.7856          | 0.6781              | 0.6670           | 0.6586 | 0.6746        |
| 0.7892        | 2.0   | 804  | 0.7083          | 0.7067              | 0.7008           | 0.6979 | 0.6983        |
| 0.6419        | 3.0   | 1206 | 0.7734          | 0.6985              | 0.6871           | 0.6773 | 0.6945        |
| 0.5582        | 4.0   | 1608 | 0.7174          | 0.7142              | 0.7154           | 0.7130 | 0.7182        |
| 0.5676        | 5.0   | 2010 | 0.7412          | 0.7098              | 0.7105           | 0.7091 | 0.7157        |
| 0.5029        | 6.0   | 2412 | 0.7501          | 0.7167              | 0.7172           | 0.7158 | 0.7219        |


### Framework versions

- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2