---
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-r
  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-r

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: 0.4382
- Meteor Score: {'meteor': 0.6824076148140416}

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 12
- 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
- lr_scheduler_warmup_steps: 8
- num_epochs: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Meteor Score                    |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------:|
| 27.8843       | 5.0   | 5    | 2.2779          | {'meteor': 0.42881843961238963} |
| 26.945        | 10.0  | 10   | 2.0505          | {'meteor': 0.501440106486018}   |
| 23.3885       | 15.0  | 15   | 1.7544          | {'meteor': 0.5479716568094775}  |
| 19.76         | 20.0  | 20   | 1.4758          | {'meteor': 0.5955711928745901}  |
| 16.4691       | 25.0  | 25   | 1.2338          | {'meteor': 0.6204550135358564}  |
| 13.6022       | 30.0  | 30   | 1.0289          | {'meteor': 0.6345912561041426}  |
| 11.1047       | 35.0  | 35   | 0.8510          | {'meteor': 0.6561421187912199}  |
| 9.0826        | 40.0  | 40   | 0.7206          | {'meteor': 0.6457048205815358}  |
| 7.4764        | 45.0  | 45   | 0.6199          | {'meteor': 0.6633570447161818}  |
| 6.2926        | 50.0  | 50   | 0.5478          | {'meteor': 0.6755789926464999}  |
| 5.4384        | 55.0  | 55   | 0.5033          | {'meteor': 0.6715844748121845}  |
| 4.8435        | 60.0  | 60   | 0.4708          | {'meteor': 0.6776793022097405}  |
| 4.4628        | 65.0  | 65   | 0.4527          | {'meteor': 0.6824716486996648}  |
| 4.2404        | 70.0  | 70   | 0.4427          | {'meteor': 0.6877583553949453}  |
| 4.1204        | 75.0  | 75   | 0.4396          | {'meteor': 0.683676455787374}   |
| 4.0752        | 80.0  | 80   | 0.4382          | {'meteor': 0.6824076148140416}  |


### Framework versions

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