ViTay-sliding / README.md
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---
library_name: transformers
license: mit
base_model: FiveC/BartTay
tags:
- generated_from_trainer
metrics:
- sacrebleu
model-index:
- name: ViTay-sliding
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. -->
# ViTay-sliding
This model is a fine-tuned version of [FiveC/BartTay](https://huggingface.co/FiveC/BartTay) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1400
- Sacrebleu: 20.7546
## 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: 16
- eval_batch_size: 16
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|
| 0.1135 | 1.0 | 3951 | 0.1640 | 16.1738 |
| 0.0954 | 2.0 | 7902 | 0.1446 | 19.4432 |
| 0.0849 | 3.0 | 11853 | 0.1400 | 20.7546 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1