metadata
library_name: transformers
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: VIT_Captioning
results: []
VIT_Captioning
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0461
- Rouge1: 0.4850
- Rouge2: 0.2566
- Rougel: 0.3589
- Rougelsum: 0.3595
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 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: 1024
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.4042 | 1.0 | 1828 | 1.7451 | 0.4622 | 0.1906 | 0.3370 | 0.3422 |
| 1.5875 | 2.0 | 3656 | 1.5933 | 0.4599 | 0.2060 | 0.3451 | 0.3472 |
| 1.3882 | 3.0 | 5484 | 1.5322 | 0.4606 | 0.2082 | 0.3422 | 0.3442 |
| 1.2415 | 4.0 | 7312 | 1.5130 | 0.4687 | 0.2208 | 0.3458 | 0.3476 |
| 1.1113 | 5.0 | 9140 | 1.5186 | 0.4630 | 0.2146 | 0.3398 | 0.3402 |
| 0.9671 | 6.0 | 10968 | 1.5683 | 0.4720 | 0.2290 | 0.3517 | 0.3520 |
| 0.8528 | 7.0 | 12796 | 1.6352 | 0.4704 | 0.2281 | 0.3491 | 0.3496 |
| 0.7555 | 8.0 | 14624 | 1.7122 | 0.4725 | 0.2305 | 0.3477 | 0.3481 |
| 0.6567 | 9.0 | 16452 | 1.7814 | 0.4763 | 0.2389 | 0.3537 | 0.3543 |
| 0.5612 | 10.0 | 18280 | 1.8528 | 0.4777 | 0.2410 | 0.3515 | 0.3516 |
| 0.4953 | 11.0 | 20108 | 1.9072 | 0.4799 | 0.2487 | 0.3562 | 0.3565 |
| 0.4445 | 12.0 | 21936 | 1.9503 | 0.4829 | 0.2514 | 0.3571 | 0.3574 |
| 0.3976 | 13.0 | 23764 | 1.9928 | 0.4834 | 0.2543 | 0.3569 | 0.3573 |
| 0.3643 | 14.0 | 25592 | 2.0249 | 0.4820 | 0.2520 | 0.3575 | 0.3581 |
| 0.3263 | 15.0 | 27420 | 2.0461 | 0.4850 | 0.2566 | 0.3589 | 0.3595 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3