---
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
- bleu
model-index:
- name: IC_ver4a_coco_swin_gpt2_1pc_1e
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# IC_ver4a_coco_swin_gpt2_1pc_1e

This model is a fine-tuned version of [](https://huggingface.co/) on the coco dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0910
- Rouge1: 29.7994
- Rouge2: 7.3652
- Rougel: 27.9817
- Rougelsum: 28.041
- Bleu: 2.5557
- Gen Len: 11.1124

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:------:|:-------:|
| 1.7489        | 0.14  | 50   | 1.2748          | 22.1874 | 2.634  | 21.043  | 21.059    | 0.0    | 11.1124 |
| 1.3067        | 0.28  | 100  | 1.1917          | 25.4818 | 4.8904 | 23.8981 | 23.981    | 2.9734 | 11.1124 |
| 1.2822        | 0.42  | 150  | 1.1982          | 24.3457 | 4.1568 | 22.512  | 22.528    | 0.0    | 11.1124 |
| 1.2584        | 0.56  | 200  | 1.1801          | 23.7424 | 3.9363 | 22.0734 | 22.0981   | 0.0    | 11.1124 |
| 1.2148        | 0.71  | 250  | 1.1412          | 25.134  | 5.0362 | 23.6681 | 23.7093   | 2.0303 | 11.1124 |
| 1.1806        | 0.85  | 300  | 1.1048          | 28.8206 | 7.4959 | 27.0534 | 27.1111   | 2.965  | 11.1124 |
| 1.2013        | 0.99  | 350  | 1.0911          | 29.6942 | 7.3408 | 27.8612 | 27.901    | 2.5222 | 11.1124 |


### Framework versions

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