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---
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
- bleu
model-index:
- name: IC_ver6d_coco_swin_gpt2_50Bpc_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_ver6d_coco_swin_gpt2_50Bpc_1e

This model is a fine-tuned version of [VK246/IC_ver6c_coco_swin_gpt2_50Apc_1e](https://huggingface.co/VK246/IC_ver6c_coco_swin_gpt2_50Apc_1e) on the coco dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7897
- Rouge1: 42.1846
- Rouge2: 16.6343
- Rougel: 38.2927
- Rougelsum: 38.2913
- Bleu: 10.4949
- 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 | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
| 0.7741        | 0.17  | 500  | 0.8245          | 40.8216 | 15.539  | 37.1564 | 37.1436   | 9.6536  | 11.3063 |
| 0.7813        | 0.34  | 1000 | 0.8155          | 41.2707 | 15.9841 | 37.4357 | 37.4254   | 10.033  | 11.3063 |
| 0.782         | 0.51  | 1500 | 0.8061          | 41.6066 | 16.0222 | 37.802  | 37.8009   | 9.9619  | 11.3063 |
| 0.79          | 0.68  | 2000 | 0.7985          | 41.6881 | 16.2489 | 37.9303 | 37.9178   | 10.3074 | 11.3063 |
| 0.7888        | 0.85  | 2500 | 0.7929          | 42.1145 | 16.5388 | 38.2401 | 38.2324   | 10.3546 | 11.3063 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3