End of training
Browse files
README.md
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs:
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step
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| 0.
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| 0.
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| 0.
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| 0.
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| 58 |
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| 0.1545 | 0.2239 | 500 | 0.1474 | 0.2791 |
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| 59 |
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| 0.119 | 0.2687 | 600 | 0.1157 | 0.2326 |
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| 60 |
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| 0.122 | 0.3135 | 700 | 0.0876 | 0.4186 |
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| 61 |
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| 0.1132 | 0.3583 | 800 | 0.0820 | 0.4593 |
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| 62 |
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| 0.1225 | 0.4030 | 900 | 0.0959 | 0.3779 |
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| 63 |
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| 0.0971 | 0.4478 | 1000 | 0.0729 | 0.4884 |
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| 64 |
-
| 0.0861 | 0.4926 | 1100 | 0.0606 | 0.5291 |
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| 65 |
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| 0.0809 | 0.5374 | 1200 | 0.0630 | 0.5174 |
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| 66 |
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| 0.06 | 0.5822 | 1300 | 0.0485 | 0.6919 |
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| 67 |
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| 0.0602 | 0.6270 | 1400 | 0.0531 | 0.6105 |
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| 68 |
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| 0.075 | 0.6717 | 1500 | 0.0452 | 0.5988 |
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| 69 |
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| 0.0477 | 0.7165 | 1600 | 0.0360 | 0.6977 |
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| 70 |
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| 0.0542 | 0.7613 | 1700 | 0.0360 | 0.7209 |
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| 71 |
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| 0.0455 | 0.8061 | 1800 | 0.0411 | 0.7151 |
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| 72 |
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| 0.0424 | 0.8509 | 1900 | 0.0377 | 0.6977 |
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| 73 |
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| 0.0334 | 0.8957 | 2000 | 0.0274 | 0.7674 |
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| 74 |
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| 0.0443 | 0.9404 | 2100 | 0.0276 | 0.7733 |
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| 75 |
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| 0.0366 | 0.9852 | 2200 | 0.0365 | 0.6977 |
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| 0.0285 | 1.0300 | 2300 | 0.0366 | 0.7384 |
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| 77 |
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| 0.031 | 1.0748 | 2400 | 0.0379 | 0.8023 |
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| 78 |
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| 0.0389 | 1.1196 | 2500 | 0.0383 | 0.6977 |
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| 79 |
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| 0.0325 | 1.1644 | 2600 | 0.0252 | 0.7442 |
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| 80 |
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| 0.0233 | 1.2091 | 2700 | 0.0229 | 0.8256 |
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| 81 |
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| 0.0304 | 1.2539 | 2800 | 0.0130 | 0.8663 |
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| 82 |
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| 0.0258 | 1.2987 | 2900 | 0.0237 | 0.8081 |
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| 83 |
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| 0.0225 | 1.3435 | 3000 | 0.0254 | 0.7616 |
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| 84 |
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| 0.0243 | 1.3883 | 3100 | 0.0230 | 0.8372 |
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| 85 |
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| 0.0244 | 1.4330 | 3200 | 0.0215 | 0.8605 |
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| 86 |
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| 0.0163 | 1.4778 | 3300 | 0.0185 | 0.8721 |
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| 87 |
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| 0.0179 | 1.5226 | 3400 | 0.0134 | 0.8605 |
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| 88 |
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| 0.0224 | 1.5674 | 3500 | 0.0325 | 0.8081 |
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| 89 |
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| 0.0123 | 1.6122 | 3600 | 0.0173 | 0.8605 |
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| 90 |
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| 0.0165 | 1.6570 | 3700 | 0.0271 | 0.8430 |
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| 91 |
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| 0.0246 | 1.7017 | 3800 | 0.0284 | 0.8023 |
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| 92 |
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| 0.0171 | 1.7465 | 3900 | 0.0189 | 0.8605 |
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| 93 |
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| 0.0163 | 1.7913 | 4000 | 0.0111 | 0.9012 |
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| 94 |
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| 0.0131 | 1.8361 | 4100 | 0.0125 | 0.9012 |
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| 95 |
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| 0.0145 | 1.8809 | 4200 | 0.0064 | 0.9419 |
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| 96 |
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| 0.0128 | 1.9257 | 4300 | 0.0105 | 0.9128 |
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| 97 |
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| 0.0227 | 1.9704 | 4400 | 0.0151 | 0.8488 |
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| 98 |
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| 0.0086 | 2.0152 | 4500 | 0.0133 | 0.9012 |
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| 99 |
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| 0.0094 | 2.0600 | 4600 | 0.0203 | 0.8663 |
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| 100 |
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| 0.0136 | 2.1048 | 4700 | 0.0231 | 0.9128 |
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| 0.0126 | 2.1496 | 4800 | 0.0297 | 0.8837 |
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| 0.0086 | 2.1944 | 4900 | 0.0159 | 0.8953 |
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| 0.0137 | 2.2391 | 5000 | 0.0107 | 0.8837 |
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| 104 |
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| 0.0129 | 2.2839 | 5100 | 0.0091 | 0.8895 |
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| 105 |
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| 0.0117 | 2.3287 | 5200 | 0.0163 | 0.9360 |
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| 106 |
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| 0.0096 | 2.3735 | 5300 | 0.0161 | 0.9186 |
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| 107 |
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| 0.0112 | 2.4183 | 5400 | 0.0220 | 0.9128 |
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| 108 |
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| 0.0086 | 2.4631 | 5500 | 0.0205 | 0.8953 |
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| 109 |
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| 0.0163 | 2.5078 | 5600 | 0.0308 | 0.8430 |
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| 0.0073 | 2.5526 | 5700 | 0.0145 | 0.8663 |
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| 0.0073 | 2.5974 | 5800 | 0.0176 | 0.9360 |
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| 112 |
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| 0.0102 | 2.6422 | 5900 | 0.0165 | 0.9128 |
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| 0.01 | 2.6870 | 6000 | 0.0152 | 0.8953 |
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| 114 |
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| 0.0084 | 2.7318 | 6100 | 0.0173 | 0.9302 |
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| 115 |
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| 0.0068 | 2.7765 | 6200 | 0.0166 | 0.9477 |
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| 116 |
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| 0.0086 | 2.8213 | 6300 | 0.0104 | 0.9302 |
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| 117 |
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| 0.0067 | 2.8661 | 6400 | 0.0215 | 0.8895 |
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| 118 |
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| 0.0056 | 2.9109 | 6500 | 0.0202 | 0.9070 |
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| 119 |
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| 0.0083 | 2.9557 | 6600 | 0.0240 | 0.8953 |
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| 120 |
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| 0.0074 | 3.0004 | 6700 | 0.0043 | 0.9419 |
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| 121 |
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| 0.0038 | 3.0452 | 6800 | 0.0163 | 0.9360 |
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| 122 |
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| 0.0032 | 3.0900 | 6900 | 0.0186 | 0.8953 |
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| 123 |
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| 0.0034 | 3.1348 | 7000 | 0.0121 | 0.9593 |
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| 124 |
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| 0.005 | 3.1796 | 7100 | 0.0064 | 0.9535 |
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| 125 |
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| 0.0043 | 3.2244 | 7200 | 0.0115 | 0.9128 |
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| 126 |
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| 0.0063 | 3.2691 | 7300 | 0.0173 | 0.9302 |
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| 127 |
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| 0.0042 | 3.3139 | 7400 | 0.0094 | 0.9012 |
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| 128 |
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| 0.0031 | 3.3587 | 7500 | 0.0129 | 0.9302 |
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| 129 |
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| 0.0053 | 3.4035 | 7600 | 0.0147 | 0.9128 |
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| 130 |
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| 0.0067 | 3.4483 | 7700 | 0.0262 | 0.9244 |
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| 131 |
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| 0.0049 | 3.4931 | 7800 | 0.0141 | 0.9419 |
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| 132 |
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| 0.0015 | 3.5378 | 7900 | 0.0261 | 0.8953 |
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| 133 |
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| 0.0052 | 3.5826 | 8000 | 0.0193 | 0.8953 |
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| 134 |
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| 0.0046 | 3.6274 | 8100 | 0.0228 | 0.9012 |
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| 135 |
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| 0.0028 | 3.6722 | 8200 | 0.0241 | 0.9070 |
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| 136 |
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| 0.0035 | 3.7170 | 8300 | 0.0152 | 0.9302 |
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| 137 |
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| 0.0051 | 3.7618 | 8400 | 0.0205 | 0.9419 |
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| 138 |
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| 0.0024 | 3.8065 | 8500 | 0.0210 | 0.9302 |
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| 139 |
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| 0.0023 | 3.8513 | 8600 | 0.0099 | 0.9477 |
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| 140 |
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| 0.0013 | 3.8961 | 8700 | 0.0123 | 0.9419 |
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| 141 |
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| 0.0025 | 3.9409 | 8800 | 0.0151 | 0.8895 |
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| 142 |
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| 0.0034 | 3.9857 | 8900 | 0.0213 | 0.9477 |
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| 143 |
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| 0.0019 | 4.0305 | 9000 | 0.0264 | 0.9012 |
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| 144 |
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| 0.0031 | 4.0752 | 9100 | 0.0226 | 0.9012 |
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| 145 |
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| 0.0021 | 4.1200 | 9200 | 0.0134 | 0.9535 |
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| 146 |
-
| 0.0028 | 4.1648 | 9300 | 0.0117 | 0.9477 |
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| 147 |
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| 0.0027 | 4.2096 | 9400 | 0.0035 | 0.9709 |
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| 148 |
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| 0.0016 | 4.2544 | 9500 | 0.0095 | 0.9128 |
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| 149 |
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| 0.0026 | 4.2991 | 9600 | 0.0204 | 0.9302 |
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| 150 |
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| 0.0016 | 4.3439 | 9700 | 0.0180 | 0.9419 |
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| 151 |
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| 0.0009 | 4.3887 | 9800 | 0.0189 | 0.9477 |
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| 152 |
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| 0.0013 | 4.4335 | 9900 | 0.0227 | 0.9360 |
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| 153 |
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| 0.0008 | 4.4783 | 10000 | 0.0223 | 0.9128 |
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| 154 |
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| 0.0016 | 4.5231 | 10100 | 0.0191 | 0.9593 |
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| 155 |
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| 0.001 | 4.5678 | 10200 | 0.0155 | 0.9709 |
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| 156 |
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| 0.002 | 4.6126 | 10300 | 0.0162 | 0.9360 |
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| 157 |
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| 0.0016 | 4.6574 | 10400 | 0.0158 | 0.9593 |
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| 158 |
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| 0.0025 | 4.7022 | 10500 | 0.0191 | 0.9535 |
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| 159 |
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| 0.0004 | 4.7470 | 10600 | 0.0130 | 0.9535 |
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| 160 |
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| 0.0012 | 4.7918 | 10700 | 0.0101 | 0.9593 |
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| 161 |
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| 0.0012 | 4.8365 | 10800 | 0.0128 | 0.9419 |
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| 162 |
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| 0.0009 | 4.8813 | 10900 | 0.0115 | 0.9535 |
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| 163 |
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| 0.0014 | 4.9261 | 11000 | 0.0117 | 0.9477 |
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| 0.0006 | 4.9709 | 11100 | 0.0113 | 0.9477 |
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### Framework versions
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This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0178
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- Accuracy: 0.9535
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 0.2
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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 | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.0025 | 0.0448 | 100 | 0.0226 | 0.9244 |
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| 0.0013 | 0.0896 | 200 | 0.0133 | 0.9244 |
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| 0.0006 | 0.1343 | 300 | 0.0205 | 0.9419 |
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| 0.0004 | 0.1791 | 400 | 0.0178 | 0.9535 |
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### Framework versions
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