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---
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: git-base-captioning
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-base-captioning
This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3575
- Wer Score: 0.8322
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:------:|:----:|:---------------:|:---------:|
| 7.8992 | 0.3540 | 20 | 7.5466 | 11.1579 |
| 5.9879 | 0.7080 | 40 | 5.6121 | 5.1946 |
| 4.1288 | 1.0619 | 60 | 3.7153 | 4.5433 |
| 2.3477 | 1.4159 | 80 | 1.9989 | 4.0242 |
| 1.0242 | 1.7699 | 100 | 0.8650 | 0.8657 |
| 0.4954 | 2.1239 | 120 | 0.4766 | 0.8676 |
| 0.3365 | 2.4779 | 140 | 0.3993 | 3.7516 |
| 0.4286 | 2.8319 | 160 | 0.3773 | 0.8336 |
| 0.2952 | 3.1858 | 180 | 0.3663 | 0.8329 |
| 0.3996 | 3.5398 | 200 | 0.3619 | 0.8224 |
| 0.2629 | 3.8938 | 220 | 0.3574 | 0.8204 |
| 0.254 | 4.2478 | 240 | 0.3555 | 0.8178 |
| 0.2642 | 4.6018 | 260 | 0.3557 | 0.8132 |
| 0.2725 | 4.9558 | 280 | 0.3533 | 0.8139 |
| 0.2746 | 5.3097 | 300 | 0.3554 | 0.8093 |
| 0.1765 | 5.6637 | 320 | 0.3561 | 0.8244 |
| 0.2981 | 6.0177 | 340 | 0.3542 | 0.8375 |
| 0.1489 | 6.3717 | 360 | 0.3567 | 0.8329 |
| 0.256 | 6.7257 | 380 | 0.3553 | 0.8362 |
| 0.1574 | 7.0796 | 400 | 0.3558 | 0.8342 |
| 0.1836 | 7.4336 | 420 | 0.3566 | 0.8336 |
| 0.1697 | 7.7876 | 440 | 0.3578 | 0.8362 |
| 0.1596 | 8.1416 | 460 | 0.3571 | 0.8414 |
| 0.1628 | 8.4956 | 480 | 0.3579 | 0.8388 |
| 0.1958 | 8.8496 | 500 | 0.3572 | 0.8362 |
| 0.1695 | 9.2035 | 520 | 0.3575 | 0.8303 |
| 0.1686 | 9.5575 | 540 | 0.3576 | 0.8336 |
| 0.2166 | 9.9115 | 560 | 0.3575 | 0.8322 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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