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--- |
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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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model-index: |
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- name: git-base-floors615images |
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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-floors615images |
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0971 |
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- Wer Score: 4.3530 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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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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| 7.0263 | 0.72 | 50 | 4.1468 | 2.9871 | |
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| 1.9906 | 1.45 | 100 | 0.2971 | 0.4260 | |
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| 0.1401 | 2.17 | 150 | 0.0827 | 2.2259 | |
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| 0.0772 | 2.9 | 200 | 0.0704 | 3.9564 | |
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| 0.0567 | 3.62 | 250 | 0.0677 | 3.6360 | |
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| 0.0501 | 4.35 | 300 | 0.0678 | 3.2940 | |
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| 0.0443 | 5.07 | 350 | 0.0664 | 3.3094 | |
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| 0.0386 | 5.8 | 400 | 0.0666 | 3.0884 | |
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| 0.035 | 6.52 | 450 | 0.0681 | 3.3818 | |
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| 0.0329 | 7.25 | 500 | 0.0667 | 3.2474 | |
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| 0.0297 | 7.97 | 550 | 0.0681 | 3.6648 | |
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| 0.0271 | 8.7 | 600 | 0.0700 | 3.9405 | |
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| 0.0257 | 9.42 | 650 | 0.0697 | 3.0393 | |
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| 0.0243 | 10.14 | 700 | 0.0701 | 3.5973 | |
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| 0.0233 | 10.87 | 750 | 0.0695 | 3.0565 | |
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| 0.0213 | 11.59 | 800 | 0.0721 | 3.6980 | |
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| 0.0203 | 12.32 | 850 | 0.0730 | 3.8883 | |
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| 0.0206 | 13.04 | 900 | 0.0718 | 4.9104 | |
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| 0.0187 | 13.77 | 950 | 0.0729 | 4.4850 | |
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| 0.0192 | 14.49 | 1000 | 0.0743 | 4.6366 | |
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| 0.0184 | 15.22 | 1050 | 0.0729 | 4.9141 | |
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| 0.0169 | 15.94 | 1100 | 0.0754 | 4.6446 | |
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| 0.0167 | 16.67 | 1150 | 0.0769 | 4.8232 | |
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| 0.0162 | 17.39 | 1200 | 0.0766 | 4.7569 | |
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| 0.0165 | 18.12 | 1250 | 0.0768 | 4.3266 | |
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| 0.0157 | 18.84 | 1300 | 0.0776 | 4.1375 | |
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| 0.0144 | 19.57 | 1350 | 0.0778 | 3.9724 | |
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| 0.015 | 20.29 | 1400 | 0.0790 | 4.7041 | |
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| 0.0146 | 21.01 | 1450 | 0.0780 | 4.5003 | |
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| 0.0137 | 21.74 | 1500 | 0.0794 | 4.2167 | |
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| 0.0141 | 22.46 | 1550 | 0.0792 | 4.4856 | |
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| 0.0137 | 23.19 | 1600 | 0.0805 | 4.2634 | |
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| 0.0137 | 23.91 | 1650 | 0.0817 | 4.4162 | |
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| 0.0127 | 24.64 | 1700 | 0.0804 | 4.0319 | |
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| 0.0127 | 25.36 | 1750 | 0.0829 | 4.3628 | |
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| 0.013 | 26.09 | 1800 | 0.0826 | 4.4211 | |
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| 0.0121 | 26.81 | 1850 | 0.0823 | 4.8932 | |
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| 0.0119 | 27.54 | 1900 | 0.0835 | 4.6636 | |
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| 0.012 | 28.26 | 1950 | 0.0842 | 3.8926 | |
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| 0.0118 | 28.99 | 2000 | 0.0844 | 3.9994 | |
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| 0.011 | 29.71 | 2050 | 0.0833 | 4.1743 | |
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| 0.0109 | 30.43 | 2100 | 0.0864 | 4.4217 | |
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| 0.0108 | 31.16 | 2150 | 0.0851 | 4.8029 | |
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| 0.0103 | 31.88 | 2200 | 0.0855 | 4.0694 | |
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| 0.01 | 32.61 | 2250 | 0.0871 | 4.3198 | |
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| 0.0102 | 33.33 | 2300 | 0.0863 | 4.4082 | |
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| 0.0099 | 34.06 | 2350 | 0.0871 | 4.2112 | |
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| 0.0094 | 34.78 | 2400 | 0.0872 | 4.1774 | |
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| 0.0092 | 35.51 | 2450 | 0.0887 | 3.9742 | |
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| 0.009 | 36.23 | 2500 | 0.0882 | 4.1958 | |
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| 0.0088 | 36.96 | 2550 | 0.0893 | 4.2591 | |
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| 0.0084 | 37.68 | 2600 | 0.0885 | 4.2983 | |
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| 0.0079 | 38.41 | 2650 | 0.0894 | 4.6550 | |
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| 0.008 | 39.13 | 2700 | 0.0904 | 4.1277 | |
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| 0.0076 | 39.86 | 2750 | 0.0908 | 3.6771 | |
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| 0.0072 | 40.58 | 2800 | 0.0912 | 4.1252 | |
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| 0.0072 | 41.3 | 2850 | 0.0908 | 4.5660 | |
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| 0.0069 | 42.03 | 2900 | 0.0917 | 3.9441 | |
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| 0.0062 | 42.75 | 2950 | 0.0924 | 4.2259 | |
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| 0.006 | 43.48 | 3000 | 0.0924 | 4.2167 | |
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| 0.0059 | 44.2 | 3050 | 0.0937 | 4.6047 | |
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| 0.0055 | 44.93 | 3100 | 0.0945 | 4.4408 | |
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| 0.0048 | 45.65 | 3150 | 0.0950 | 3.9871 | |
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| 0.0048 | 46.38 | 3200 | 0.0952 | 4.2259 | |
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| 0.0046 | 47.1 | 3250 | 0.0962 | 4.2204 | |
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| 0.0042 | 47.83 | 3300 | 0.0963 | 4.2750 | |
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| 0.0037 | 48.55 | 3350 | 0.0971 | 4.1891 | |
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| 0.0039 | 49.28 | 3400 | 0.0970 | 4.3100 | |
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| 0.0036 | 50.0 | 3450 | 0.0971 | 4.3530 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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