---
library_name: transformers
license: mit
base_model: microsoft/git-large-r-coco
tags:
- generated_from_trainer
datasets:
- imagefolder
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: 3.9193
- Meteor Score: {'meteor': 0.3883164385938583}

## 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: 8
- total_train_batch_size: 64
- 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: 5
- num_epochs: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Meteor Score                     |
|:-------------:|:-------:|:----:|:---------------:|:--------------------------------:|
| 92.0222       | 3.3333  | 5    | 10.6210         | {'meteor': 0.05527200117295446}  |
| 80.4987       | 6.6667  | 10   | 9.3234          | {'meteor': 0.054478429471574795} |
| 70.872        | 10.0    | 15   | 7.9867          | {'meteor': 0.06444810159110426}  |
| 61.8948       | 13.3333 | 20   | 7.1539          | {'meteor': 0.10729657965271497}  |
| 55.8843       | 16.6667 | 25   | 6.5323          | {'meteor': 0.1313795489011057}   |
| 51.3796       | 20.0    | 30   | 6.0059          | {'meteor': 0.1667987247524706}   |
| 47.2696       | 23.3333 | 35   | 5.5433          | {'meteor': 0.1780717354914205}   |
| 43.8752       | 26.6667 | 40   | 5.1460          | {'meteor': 0.29042241595126117}  |
| 40.8073       | 30.0    | 45   | 4.8067          | {'meteor': 0.34065022984874654}  |
| 38.3594       | 33.3333 | 50   | 4.5292          | {'meteor': 0.37185069963423434}  |
| 36.2548       | 36.6667 | 55   | 4.3103          | {'meteor': 0.3764524310032932}   |
| 34.7935       | 40.0    | 60   | 4.1477          | {'meteor': 0.38111013533600185}  |
| 33.6518       | 43.3333 | 65   | 4.0357          | {'meteor': 0.3851995459070333}   |
| 32.8234       | 46.6667 | 70   | 3.9670          | {'meteor': 0.38872719984995613}  |
| 32.4724       | 50.0    | 75   | 3.9318          | {'meteor': 0.3883164385938583}   |
| 32.2541       | 53.3333 | 80   | 3.9193          | {'meteor': 0.3883164385938583}   |


### Framework versions

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