vit-gpt2-rocov22-ct-finetuned
This model is a fine-tuned version of nlpconnect/vit-gpt2-image-captioning on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3215
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: 8
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4502 | 1.0 | 1440 | 1.4252 |
| 1.392 | 2.0 | 2880 | 1.3534 |
| 1.2814 | 3.0 | 4320 | 1.3246 |
| 1.22 | 4.0 | 5760 | 1.3164 |
| 1.1829 | 5.0 | 7200 | 1.3215 |
Framework versions
- Transformers 4.56.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0