git-base-one-entrance-dungeons
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: 0.0219
- Wer Score: 1.2
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 100
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Score |
---|---|---|---|---|
0.025 | 5.0 | 10 | 0.0412 | 18.6 |
0.0225 | 10.0 | 20 | 0.0377 | 18.8 |
0.0182 | 15.0 | 30 | 0.0377 | 20.6 |
0.0135 | 20.0 | 40 | 0.0337 | 21.2 |
0.0095 | 25.0 | 50 | 0.0314 | 17.0 |
0.0067 | 30.0 | 60 | 0.0256 | 17.0 |
0.0054 | 35.0 | 70 | 0.0177 | 5.8 |
0.006 | 40.0 | 80 | 0.0240 | 37.8 |
0.0063 | 45.0 | 90 | 0.0213 | 0.2 |
0.0032 | 50.0 | 100 | 0.0222 | 1.8 |
0.0021 | 55.0 | 110 | 0.0210 | 1.6 |
0.0015 | 60.0 | 120 | 0.0203 | 2.6 |
0.0012 | 65.0 | 130 | 0.0211 | 1.4 |
0.0011 | 70.0 | 140 | 0.0217 | 1.4 |
0.001 | 75.0 | 150 | 0.0218 | 1.2 |
0.0009 | 80.0 | 160 | 0.0219 | 1.2 |
0.0009 | 85.0 | 170 | 0.0219 | 1.2 |
0.0009 | 90.0 | 180 | 0.0219 | 1.2 |
0.0009 | 95.0 | 190 | 0.0219 | 1.2 |
0.0009 | 100.0 | 200 | 0.0219 | 1.2 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for griffio/git-base-one-entrance-dungeons
Base model
microsoft/git-base