---
base_model: VK246/IC_ver6L_coco_swin_gpt2_50B_1e
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
model-index:
- name: IC_ver6M_coco_swin_gpt2_50A_1e
  results: []
---

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# IC_ver6M_coco_swin_gpt2_50A_1e

This model is a fine-tuned version of [VK246/IC_ver6L_coco_swin_gpt2_50B_1e](https://huggingface.co/VK246/IC_ver6L_coco_swin_gpt2_50B_1e) on the coco dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8502
- Cider: 74.2614
- Rouge1: 41.2346
- Rouge2: 15.6726
- Rougel: 37.3373
- Rougelsum: 37.3448
- Bleu-1: 42.1725
- Bleu-2: 24.0988
- Bleu-3: 15.0597
- Bleu-4: 9.8745
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:------:|:-------:|
| 0.4052        | 0.34  | 1000 | 0.9934          | 68.6639 | 39.9165 | 14.5681 | 36.2437 | 36.2466   | 41.4603 | 23.2118 | 14.2892 | 9.3187 | 11.2806 |
| 0.5281        | 0.68  | 2000 | 0.8502          | 74.2614 | 41.2346 | 15.6726 | 37.3373 | 37.3448   | 42.1725 | 24.0988 | 15.0597 | 9.8745 | 11.2806 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3