IC_ver6I_coco_swin_gpt2_50A_1e
This model is a fine-tuned version of VK246/IC_ver6H_coco_swin_gpt2_50B_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.8003
- Cider: 36.4847
- Rouge1: 41.9392
- Rouge2: 16.4156
- Rougel: 38.0808
- Rougelsum: 38.0721
- Bleu-1: 42.8624
- Bleu-2: 24.8647
- Bleu-3: 15.7144
- Bleu-4: 10.4434
- Gen Len: 11.2806
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: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Cider | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Gen Len |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5622 | 0.34 | 1000 | 0.8598 | 16.5035 | 41.0303 | 15.4795 | 37.2917 | 37.2896 | 41.7661 | 23.7724 | 14.7804 | 9.5941 | 11.2806 |
| 0.639 | 0.68 | 2000 | 0.8003 | 36.4847 | 41.9392 | 16.4156 | 38.0808 | 38.0721 | 42.8624 | 24.8647 | 15.7144 | 10.4434 | 11.2806 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3