metadata
base_model: VK246/IC_ver6G_coco_swin_gpt2_50A_1e
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
model-index:
- name: IC_ver6H_coco_swin_gpt2_50B_1e
results: []
IC_ver6H_coco_swin_gpt2_50B_1e
This model is a fine-tuned version of VK246/IC_ver6G_coco_swin_gpt2_50A_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.7969
- Cider: 7.3588
- Rouge1: 41.9295
- Rouge2: 16.3455
- Rougel: 37.9811
- Rougelsum: 37.9766
- Bleu-1: 42.8743
- Bleu-2: 24.7756
- Bleu-3: 15.6692
- Bleu-4: 10.4429
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6159 | 0.34 | 1000 | 0.8323 | 6.7172 | 41.0274 | 15.5809 | 37.2211 | 37.2045 | 42.2207 | 24.0365 | 15.0562 | 9.9118 | 11.3063 |
| 0.6802 | 0.68 | 2000 | 0.7969 | 7.3588 | 41.9295 | 16.3455 | 37.9811 | 37.9766 | 42.8743 | 24.7756 | 15.6692 | 10.4429 | 11.3063 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3