---
library_name: transformers
license: bsd-3-clause
base_model: shyamgv/blip-image-captioning-large-shyam
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: blip-image-captioning-large-shyam-shyam
  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. -->

# blip-image-captioning-large-shyam-shyam

This model is a fine-tuned version of [shyamgv/blip-image-captioning-large-shyam](https://huggingface.co/shyamgv/blip-image-captioning-large-shyam) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0044
- Wer Score: 0.1111

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Score |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 0.0104        | 2.9412  | 50   | 0.0041          | 0.1111    |
| 0.0025        | 5.8824  | 100  | 0.0049          | 0.1111    |
| 0.0003        | 8.8235  | 150  | 0.0056          | 0.1667    |
| 0.0002        | 11.7647 | 200  | 0.0045          | 0.1111    |
| 0.0001        | 14.7059 | 250  | 0.0044          | 0.1111    |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0