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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
should probably proofread and complete it, then remove this comment. -->
# 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
|