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---
base_model: VK246/IC_ver6e_coco_swin_gpt2_50Apc_1e
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
model-index:
- name: IC_ver6F_coco_swin_gpt2_50B_1e
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# IC_ver6F_coco_swin_gpt2_50B_1e
This model is a fine-tuned version of [VK246/IC_ver6e_coco_swin_gpt2_50Apc_1e](https://huggingface.co/VK246/IC_ver6e_coco_swin_gpt2_50Apc_1e) on the coco dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7799
- Cider: 5.8986
- Rouge1: 42.1787
- Rouge2: 16.6289
- Rougel: 38.245
- Rougelsum: 38.236
- Bleu-1: 43.2152
- Bleu-2: 25.0563
- Bleu-3: 15.845
- Bleu-4: 10.5042
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:|
| 0.6972 | 0.34 | 1000 | 0.8128 | 5.8314 | 41.3992 | 16.1278 | 37.5675 | 37.5537 | 42.6637 | 24.5815 | 15.5018 | 10.2465 | 11.3063 |
| 0.7318 | 0.68 | 2000 | 0.7912 | 6.9716 | 41.8244 | 16.3282 | 37.9594 | 37.9525 | 42.7623 | 24.7305 | 15.6458 | 10.4067 | 11.3063 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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