vit-gpt2-rocov2-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: 4.7354
- Rouge1: 13.6823
- Rougel: 11.8453
- Meteor: 6.5068
- Bleu: 845.0311
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rougel | Meteor | Bleu |
|---|---|---|---|---|---|---|---|
| 2.3859 | 1.0 | 180 | 5.0138 | 13.2987 | 11.4445 | 6.7696 | 926.3986 |
| 2.4285 | 2.0 | 360 | 4.8876 | 12.4047 | 11.0529 | 5.1461 | 1055.2670 |
| 2.3733 | 3.0 | 540 | 4.8102 | 12.7421 | 11.3659 | 5.9015 | 845.0311 |
| 2.3082 | 4.0 | 720 | 4.7644 | 14.1592 | 12.1093 | 6.8138 | 986.4703 |
| 2.3019 | 5.0 | 900 | 4.7465 | 12.7685 | 11.0803 | 5.9356 | 845.0311 |
| 2.245 | 6.0 | 1080 | 4.7354 | 13.6823 | 11.8453 | 6.5068 | 845.0311 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.0