---
base_model: VK246/IC_ver6J_coco_swin_gpt2_50B_1e
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
model-index:
- name: IC_ver6K_coco_swin_gpt2_50A_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_ver6K_coco_swin_gpt2_50A_1e

This model is a fine-tuned version of [VK246/IC_ver6J_coco_swin_gpt2_50B_1e](https://huggingface.co/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