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IC_ver6K_coco_swin_gpt2_50A_1e
This model is a fine-tuned version of VK246/IC_ver6J_coco_swin_gpt2_50B_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.8220
- Cider: 75.3012
- Rouge1: 41.577
- Rouge2: 16.0357
- Rougel: 37.7284
- Rougelsum: 37.7314
- Bleu-1: 42.4688
- Bleu-2: 24.4386
- Bleu-3: 15.3819
- Bleu-4: 10.1667
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4803 | 0.34 | 1000 | 0.9220 | 69.7834 | 40.3936 | 14.9568 | 36.6495 | 36.6487 | 41.6496 | 23.4287 | 14.4546 | 9.3691 | 11.2806 |
| 0.5848 | 0.68 | 2000 | 0.8220 | 75.3012 | 41.577 | 16.0357 | 37.7284 | 37.7314 | 42.4688 | 24.4386 | 15.3819 | 10.1667 | 11.2806 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
