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library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-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. -->
# roberta-sentiment
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2590
- F1 Macro: 0.6890
- F1 Weighted: 0.6901
- Accuracy: 0.6889
- Precision Macro: 0.6897
- Recall Macro: 0.6887
## 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: 4
- eval_batch_size: 4
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | Accuracy | Precision Macro | Recall Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:---------------:|:------------:|
| 1.0468 | 1.0 | 961 | 1.0346 | 0.5895 | 0.5948 | 0.5963 | 0.5980 | 0.5862 |
| 0.9324 | 2.0 | 1922 | 0.8973 | 0.6675 | 0.6697 | 0.6743 | 0.6670 | 0.6768 |
| 0.7848 | 3.0 | 2883 | 0.9689 | 0.6599 | 0.6632 | 0.6712 | 0.6624 | 0.6652 |
| 0.7983 | 4.0 | 3844 | 1.3608 | 0.6753 | 0.6805 | 0.6805 | 0.6889 | 0.6701 |
| 0.7084 | 5.0 | 4805 | 1.3093 | 0.6906 | 0.6922 | 0.6899 | 0.6938 | 0.6891 |
| 0.5763 | 6.0 | 5766 | 1.7146 | 0.6799 | 0.6830 | 0.6805 | 0.6857 | 0.6768 |
| 0.4508 | 7.0 | 6727 | 2.0875 | 0.6738 | 0.6773 | 0.6795 | 0.6770 | 0.6726 |
| 0.2905 | 8.0 | 7688 | 2.2861 | 0.6676 | 0.6700 | 0.6670 | 0.6709 | 0.6669 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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