metadata
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: Beit_PhoBart
results: []
Beit_PhoBart
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5865
- Bleu-4: 0.0954
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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_steps: 300
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu-4 |
|---|---|---|---|---|
| No log | 1.0 | 236 | 1.7574 | 0.0672 |
| 1.9578 | 2.0 | 472 | 1.6226 | 0.0748 |
| 1.5495 | 3.0 | 708 | 1.5523 | 0.0796 |
| 1.3763 | 4.0 | 944 | 1.4998 | 0.0821 |
| 1.3763 | 5.0 | 1180 | 1.4815 | 0.0881 |
| 1.2355 | 6.0 | 1416 | 1.4835 | 0.0875 |
| 1.1027 | 7.0 | 1652 | 1.4790 | 0.0926 |
| 0.9865 | 8.0 | 1888 | 1.5128 | 0.0925 |
| 0.884 | 9.0 | 2124 | 1.5453 | 0.0956 |
| 0.884 | 10.0 | 2360 | 1.5865 | 0.0954 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3