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---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm-roberta-large-ojk-issue
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-ojk-issue
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: 1.8954
- Accuracy: 0.4424
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 0.2
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.8197 | 1.0 | 80 | 2.7321 | 0.0997 |
| 2.779 | 2.0 | 160 | 2.7132 | 0.0685 |
| 2.7229 | 3.0 | 240 | 2.7197 | 0.1402 |
| 2.581 | 4.0 | 320 | 2.5344 | 0.2181 |
| 2.4379 | 5.0 | 400 | 2.3477 | 0.2399 |
| 2.2182 | 6.0 | 480 | 2.2080 | 0.3146 |
| 1.8611 | 7.0 | 560 | 2.0024 | 0.4112 |
| 1.7581 | 8.0 | 640 | 1.8954 | 0.4424 |
| 1.5059 | 9.0 | 720 | 1.8806 | 0.4206 |
| 1.2983 | 10.0 | 800 | 1.8553 | 0.4143 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
|