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library_name: transformers
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: Tokenization-large-lr1e-5
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. -->
# Tokenization-large-lr1e-5
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0254
## 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: 32
- eval_batch_size: 8
- 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
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.4327 | 1.0 | 14289 | 1.2043 |
| 1.2143 | 2.0 | 28578 | 1.0653 |
| 1.1104 | 3.0 | 42867 | 1.0254 |
### Framework versions
- Transformers 4.56.0
- Pytorch 2.8.0+cu129
- Datasets 5.0.0
- Tokenizers 0.22.0
|