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--- |
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library_name: transformers |
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license: mit |
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base_model: microsoft/git-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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model-index: |
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- name: git-base-one-entrance-dungeons-20 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# git-base-one-entrance-dungeons-20 |
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co./microsoft/git-base) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0115 |
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- Wer Score: 0.2812 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Score | |
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|:-------------:|:-------:|:----:|:---------------:|:---------:| |
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| 0.0112 | 0.6061 | 10 | 0.0108 | 0.2812 | |
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| 0.0094 | 1.2121 | 20 | 0.0105 | 0.25 | |
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| 0.0109 | 1.8182 | 30 | 0.0114 | 0.2656 | |
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| 0.0112 | 2.4242 | 40 | 0.0103 | 0.25 | |
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| 0.0114 | 3.0303 | 50 | 0.0108 | 0.2812 | |
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| 0.0107 | 3.6364 | 60 | 0.0113 | 0.2812 | |
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| 0.0119 | 4.2424 | 70 | 0.0108 | 0.2344 | |
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| 0.0121 | 4.8485 | 80 | 0.0106 | 0.2344 | |
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| 0.0115 | 5.4545 | 90 | 0.0112 | 0.25 | |
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| 0.0126 | 6.0606 | 100 | 0.0107 | 0.25 | |
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| 0.0118 | 6.6667 | 110 | 0.0119 | 0.25 | |
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| 0.0116 | 7.2727 | 120 | 0.0105 | 0.2188 | |
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| 0.0122 | 7.8788 | 130 | 0.0105 | 0.2656 | |
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| 0.0103 | 8.4848 | 140 | 0.0109 | 0.2812 | |
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| 0.0102 | 9.0909 | 150 | 0.0107 | 0.25 | |
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| 0.0099 | 9.6970 | 160 | 0.0118 | 0.25 | |
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| 0.0091 | 10.3030 | 170 | 0.0113 | 0.2656 | |
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| 0.0095 | 10.9091 | 180 | 0.0109 | 0.2656 | |
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| 0.0093 | 11.5152 | 190 | 0.0114 | 0.25 | |
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| 0.0088 | 12.1212 | 200 | 0.0119 | 0.2812 | |
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| 0.0091 | 12.7273 | 210 | 0.0123 | 0.2812 | |
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| 0.009 | 13.3333 | 220 | 0.0119 | 0.2969 | |
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| 0.0092 | 13.9394 | 230 | 0.0112 | 0.25 | |
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| 0.0084 | 14.5455 | 240 | 0.0116 | 0.2812 | |
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| 0.009 | 15.1515 | 250 | 0.0118 | 0.2969 | |
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| 0.0077 | 15.7576 | 260 | 0.0120 | 0.2656 | |
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| 0.008 | 16.3636 | 270 | 0.0116 | 0.2344 | |
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| 0.0079 | 16.9697 | 280 | 0.0115 | 0.2812 | |
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| 0.0077 | 17.5758 | 290 | 0.0115 | 0.2812 | |
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| 0.0079 | 18.1818 | 300 | 0.0116 | 0.2812 | |
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| 0.0084 | 18.7879 | 310 | 0.0115 | 0.2812 | |
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| 0.0085 | 19.3939 | 320 | 0.0115 | 0.2812 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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