transformers tensorboard safetensors vision-encoder-decoder generated_from_trainer dataset:coco endpoints_compatible region:us
---
tags:
- generated_from_trainer
datasets:
- coco
metrics:
- rouge
- bleu
model-index:
- name: vit-swin-base-224-gpt2-image-captioning
  results: []
---

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# vit-swin-base-224-gpt2-image-captioning

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: 0.7890
- Rouge1: 42.0529
- Rouge2: 16.4913
- Rougel: 38.2259
- Rougelsum: 38.2263
- Bleu: 10.4655
- Gen Len: 11.2805

## 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: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
| 1.0917        | 0.11  | 2000  | 0.9769          | 35.665  | 11.3651 | 32.6028 | 32.6147   | 6.4011  | 11.2805 |
| 0.9644        | 0.23  | 4000  | 0.9323          | 36.4642 | 11.9725 | 33.3929 | 33.4005   | 6.7382  | 11.2805 |
| 0.928         | 0.34  | 6000  | 0.9039          | 37.7457 | 12.7961 | 34.3931 | 34.4057   | 7.3402  | 11.2805 |
| 0.9152        | 0.45  | 8000  | 0.8811          | 38.123  | 13.357  | 34.8585 | 34.8523   | 7.7891  | 11.2805 |
| 0.8959        | 0.57  | 10000 | 0.8662          | 38.9917 | 13.9511 | 35.554  | 35.5647   | 8.4609  | 11.2805 |
| 0.8765        | 0.68  | 12000 | 0.8591          | 38.637  | 13.7212 | 35.2989 | 35.3135   | 8.1407  | 11.2805 |
| 0.8633        | 0.79  | 14000 | 0.8446          | 39.4395 | 14.1544 | 35.95   | 35.9525   | 8.5487  | 11.2805 |
| 0.8587        | 0.91  | 16000 | 0.8335          | 39.8372 | 14.7238 | 36.4748 | 36.4642   | 9.0466  | 11.2805 |
| 0.8439        | 1.02  | 18000 | 0.8245          | 40.3348 | 15.204  | 36.7237 | 36.7337   | 9.4411  | 11.2805 |
| 0.8001        | 1.13  | 20000 | 0.8197          | 40.5803 | 15.303  | 36.8781 | 36.8743   | 9.5544  | 11.2805 |
| 0.7879        | 1.25  | 22000 | 0.8137          | 40.4973 | 15.331  | 36.9524 | 36.9486   | 9.513   | 11.2805 |
| 0.7789        | 1.36  | 24000 | 0.8084          | 41.29   | 16.0119 | 37.6282 | 37.631    | 9.8994  | 11.2805 |
| 0.7792        | 1.47  | 26000 | 0.8030          | 41.1957 | 15.7504 | 37.4912 | 37.4884   | 9.7022  | 11.2805 |
| 0.7686        | 1.58  | 28000 | 0.7992          | 41.4362 | 15.9288 | 37.6629 | 37.6641   | 10.0447 | 11.2805 |
| 0.764         | 1.7   | 30000 | 0.7950          | 41.9439 | 16.4393 | 38.1183 | 38.1188   | 10.3535 | 11.2805 |
| 0.7587        | 1.81  | 32000 | 0.7926          | 41.7549 | 16.242  | 37.9677 | 37.9679   | 10.2014 | 11.2805 |
| 0.7502        | 1.92  | 34000 | 0.7899          | 42.0402 | 16.453  | 38.1822 | 38.1899   | 10.3883 | 11.2805 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
