---
base_model: microsoft/git-large-r-coco
datasets:
- imagefolder
library_name: transformers
license: mit
tags:
- generated_from_trainer
model-index:
- name: git-large-r-coco-IDB_ADv1_COCOv6-rv2
  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. -->

# git-large-r-coco-IDB_ADv1_COCOv6-rv2

This model is a fine-tuned version of [microsoft/git-large-r-coco](https://huggingface.co/microsoft/git-large-r-coco) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0934
- Meteor Score: {'meteor': 0.6849337864778346}

## 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: 3e-05
- train_batch_size: 6
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 96
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Meteor Score                   |
|:-------------:|:-----:|:----:|:---------------:|:------------------------------:|
| 0.7802        | 5.0   | 5    | 0.1019          | {'meteor': 0.6667354024231188} |
| 0.756         | 10.0  | 10   | 0.1006          | {'meteor': 0.6766394690979587} |
| 0.7057        | 15.0  | 15   | 0.0972          | {'meteor': 0.6774630113691023} |
| 0.6349        | 20.0  | 20   | 0.0934          | {'meteor': 0.6849337864778346} |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.20.2