---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# IC_ver6L_coco_swin_gpt2_50B_1e

This model is a fine-tuned version of [VK246/IC_ver6K_coco_swin_gpt2_50A_1e](https://huggingface.co/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