metadata
base_model: VK246/IC_ver6K_coco_swin_gpt2_50A_1e
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
model-index:
- name: IC_ver6L_coco_swin_gpt2_50B_1e
results: []
IC_ver6L_coco_swin_gpt2_50B_1e
This model is a fine-tuned version of VK246/IC_ver6K_coco_swin_gpt2_50A_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.8371
- Cider: 72.6054
- Rouge1: 41.2906
- Rouge2: 15.8851
- Rougel: 37.3963
- Rougelsum: 37.4014
- Bleu-1: 42.3937
- Bleu-2: 24.3104
- Bleu-3: 15.291
- Bleu-4: 10.0894
- Gen Len: 11.3063
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4535 | 0.34 | 1000 | 0.9282 | 70.2558 | 40.6455 | 15.1383 | 36.6998 | 36.6999 | 41.838 | 23.6151 | 14.6823 | 9.6083 | 11.3063 |
| 0.5716 | 0.68 | 2000 | 0.8371 | 72.6054 | 41.2906 | 15.8851 | 37.3963 | 37.4014 | 42.3937 | 24.3104 | 15.291 | 10.0894 | 11.3063 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3