Swin_BART_KTVIC
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1684
- Bleu-4: 0.2074
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 | 1.4136 | 0.1220 |
1.9745 | 2.0 | 472 | 1.2818 | 0.1443 |
1.3205 | 3.0 | 708 | 1.2124 | 0.1686 |
1.1231 | 4.0 | 944 | 1.1763 | 0.1860 |
1.1231 | 5.0 | 1180 | 1.1625 | 0.1949 |
0.9658 | 6.0 | 1416 | 1.1590 | 0.2025 |
0.8276 | 7.0 | 1652 | 1.1684 | 0.2074 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Downloads last month
- 17
Inference API (serverless) does not yet support transformers models for this pipeline type.