image_caption_git-base_pokemon-blip-captions_finetune
This model is a fine-tuned version of microsoft/git-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0382
- Wer Score: 2.2973
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Score |
---|---|---|---|---|
7.1973 | 4.17 | 50 | 4.4470 | 21.4968 |
2.3075 | 8.33 | 100 | 0.4412 | 10.5882 |
0.1359 | 12.5 | 150 | 0.0328 | 1.5792 |
0.0188 | 16.67 | 200 | 0.0293 | 1.1776 |
0.0068 | 20.83 | 250 | 0.0329 | 2.0798 |
0.0023 | 25.0 | 300 | 0.0354 | 2.6898 |
0.0014 | 29.17 | 350 | 0.0365 | 2.5650 |
0.0012 | 33.33 | 400 | 0.0374 | 2.4118 |
0.0011 | 37.5 | 450 | 0.0377 | 2.4080 |
0.001 | 41.67 | 500 | 0.0381 | 2.3745 |
0.0009 | 45.83 | 550 | 0.0382 | 2.2857 |
0.0009 | 50.0 | 600 | 0.0382 | 2.2973 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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