---
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: []
---

<!-- 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_ver6H_coco_swin_gpt2_50B_1e

This model is a fine-tuned version of [VK246/IC_ver6G_coco_swin_gpt2_50A_1e](https://huggingface.co/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