---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: sap_predictions_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sap_predictions_model

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: 6.3177
- Accuracy: 0.1599
- F1: 0.0713

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use adamw_torch 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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 8.7072        | 0.6425 | 1000 | 8.5615          | 0.0156   | 0.0018 |
| 7.9463        | 1.2846 | 2000 | 7.8865          | 0.0445   | 0.0110 |
| 7.3576        | 1.9271 | 3000 | 7.2356          | 0.1019   | 0.0376 |
| 6.8566        | 2.5692 | 4000 | 6.7092          | 0.1424   | 0.0591 |
| 6.3983        | 3.2114 | 5000 | 6.3177          | 0.1599   | 0.0713 |
| 6.1392        | 3.8538 | 6000 | 6.0647          | 0.1756   | 0.0821 |
| 6.0378        | 4.4960 | 7000 | 5.9330          | 0.1819   | 0.0866 |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1