| --- |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: categor_ai |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # categor_ai |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6307 |
| - Accuracy: 0.8901 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 100 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 14 | 2.4323 | 0.4615 | |
| | No log | 2.0 | 28 | 2.0883 | 0.5495 | |
| | No log | 3.0 | 42 | 1.7465 | 0.7033 | |
| | No log | 4.0 | 56 | 1.4428 | 0.7363 | |
| | No log | 5.0 | 70 | 1.1838 | 0.8242 | |
| | No log | 6.0 | 84 | 0.9881 | 0.8132 | |
| | No log | 7.0 | 98 | 0.8446 | 0.8571 | |
| | No log | 8.0 | 112 | 0.7304 | 0.8791 | |
| | No log | 9.0 | 126 | 0.6456 | 0.8681 | |
| | No log | 10.0 | 140 | 0.6267 | 0.8352 | |
| | No log | 11.0 | 154 | 0.5656 | 0.8791 | |
| | No log | 12.0 | 168 | 0.5412 | 0.8901 | |
| | No log | 13.0 | 182 | 0.5301 | 0.8901 | |
| | No log | 14.0 | 196 | 0.5190 | 0.8791 | |
| | No log | 15.0 | 210 | 0.5175 | 0.8901 | |
| | No log | 16.0 | 224 | 0.5295 | 0.8681 | |
| | No log | 17.0 | 238 | 0.5147 | 0.8901 | |
| | No log | 18.0 | 252 | 0.5094 | 0.8901 | |
| | No log | 19.0 | 266 | 0.5130 | 0.8791 | |
| | No log | 20.0 | 280 | 0.5212 | 0.8901 | |
| | No log | 21.0 | 294 | 0.5421 | 0.8791 | |
| | No log | 22.0 | 308 | 0.5439 | 0.8791 | |
| | No log | 23.0 | 322 | 0.5516 | 0.8791 | |
| | No log | 24.0 | 336 | 0.5544 | 0.8791 | |
| | No log | 25.0 | 350 | 0.5441 | 0.8901 | |
| | No log | 26.0 | 364 | 0.5497 | 0.8901 | |
| | No log | 27.0 | 378 | 0.5502 | 0.8791 | |
| | No log | 28.0 | 392 | 0.5345 | 0.8901 | |
| | No log | 29.0 | 406 | 0.5444 | 0.8901 | |
| | No log | 30.0 | 420 | 0.5489 | 0.8901 | |
| | No log | 31.0 | 434 | 0.5838 | 0.8681 | |
| | No log | 32.0 | 448 | 0.5444 | 0.9011 | |
| | No log | 33.0 | 462 | 0.6005 | 0.8681 | |
| | No log | 34.0 | 476 | 0.5633 | 0.8901 | |
| | No log | 35.0 | 490 | 0.5701 | 0.8791 | |
| | 0.4178 | 36.0 | 504 | 0.5805 | 0.8901 | |
| | 0.4178 | 37.0 | 518 | 0.5919 | 0.8791 | |
| | 0.4178 | 38.0 | 532 | 0.5729 | 0.8901 | |
| | 0.4178 | 39.0 | 546 | 0.5805 | 0.8901 | |
| | 0.4178 | 40.0 | 560 | 0.5940 | 0.8901 | |
| | 0.4178 | 41.0 | 574 | 0.5816 | 0.8901 | |
| | 0.4178 | 42.0 | 588 | 0.5754 | 0.8901 | |
| | 0.4178 | 43.0 | 602 | 0.5838 | 0.8901 | |
| | 0.4178 | 44.0 | 616 | 0.5901 | 0.8901 | |
| | 0.4178 | 45.0 | 630 | 0.5942 | 0.8901 | |
| | 0.4178 | 46.0 | 644 | 0.5922 | 0.8901 | |
| | 0.4178 | 47.0 | 658 | 0.5908 | 0.8901 | |
| | 0.4178 | 48.0 | 672 | 0.5921 | 0.8901 | |
| | 0.4178 | 49.0 | 686 | 0.5916 | 0.8901 | |
| | 0.4178 | 50.0 | 700 | 0.6024 | 0.8901 | |
| | 0.4178 | 51.0 | 714 | 0.6012 | 0.8901 | |
| | 0.4178 | 52.0 | 728 | 0.5998 | 0.8901 | |
| | 0.4178 | 53.0 | 742 | 0.6031 | 0.8901 | |
| | 0.4178 | 54.0 | 756 | 0.5967 | 0.8901 | |
| | 0.4178 | 55.0 | 770 | 0.5950 | 0.8901 | |
| | 0.4178 | 56.0 | 784 | 0.6018 | 0.8901 | |
| | 0.4178 | 57.0 | 798 | 0.5989 | 0.8901 | |
| | 0.4178 | 58.0 | 812 | 0.5945 | 0.8901 | |
| | 0.4178 | 59.0 | 826 | 0.5948 | 0.8901 | |
| | 0.4178 | 60.0 | 840 | 0.5930 | 0.8901 | |
| | 0.4178 | 61.0 | 854 | 0.5961 | 0.8901 | |
| | 0.4178 | 62.0 | 868 | 0.6010 | 0.8901 | |
| | 0.4178 | 63.0 | 882 | 0.5973 | 0.8901 | |
| | 0.4178 | 64.0 | 896 | 0.5997 | 0.8901 | |
| | 0.4178 | 65.0 | 910 | 0.6016 | 0.8901 | |
| | 0.4178 | 66.0 | 924 | 0.6069 | 0.8901 | |
| | 0.4178 | 67.0 | 938 | 0.6095 | 0.8901 | |
| | 0.4178 | 68.0 | 952 | 0.6117 | 0.8901 | |
| | 0.4178 | 69.0 | 966 | 0.6160 | 0.8901 | |
| | 0.4178 | 70.0 | 980 | 0.6166 | 0.8901 | |
| | 0.4178 | 71.0 | 994 | 0.6177 | 0.8901 | |
| | 0.0153 | 72.0 | 1008 | 0.6172 | 0.8901 | |
| | 0.0153 | 73.0 | 1022 | 0.6190 | 0.8901 | |
| | 0.0153 | 74.0 | 1036 | 0.6213 | 0.8901 | |
| | 0.0153 | 75.0 | 1050 | 0.6220 | 0.8901 | |
| | 0.0153 | 76.0 | 1064 | 0.6204 | 0.8901 | |
| | 0.0153 | 77.0 | 1078 | 0.6193 | 0.8901 | |
| | 0.0153 | 78.0 | 1092 | 0.6198 | 0.8901 | |
| | 0.0153 | 79.0 | 1106 | 0.6235 | 0.8901 | |
| | 0.0153 | 80.0 | 1120 | 0.6260 | 0.8901 | |
| | 0.0153 | 81.0 | 1134 | 0.6271 | 0.8901 | |
| | 0.0153 | 82.0 | 1148 | 0.6290 | 0.8901 | |
| | 0.0153 | 83.0 | 1162 | 0.6288 | 0.8901 | |
| | 0.0153 | 84.0 | 1176 | 0.6298 | 0.8901 | |
| | 0.0153 | 85.0 | 1190 | 0.6301 | 0.8901 | |
| | 0.0153 | 86.0 | 1204 | 0.6324 | 0.8901 | |
| | 0.0153 | 87.0 | 1218 | 0.6332 | 0.8901 | |
| | 0.0153 | 88.0 | 1232 | 0.6333 | 0.8901 | |
| | 0.0153 | 89.0 | 1246 | 0.6347 | 0.8901 | |
| | 0.0153 | 90.0 | 1260 | 0.6337 | 0.8901 | |
| | 0.0153 | 91.0 | 1274 | 0.6332 | 0.8901 | |
| | 0.0153 | 92.0 | 1288 | 0.6329 | 0.8901 | |
| | 0.0153 | 93.0 | 1302 | 0.6316 | 0.8901 | |
| | 0.0153 | 94.0 | 1316 | 0.6315 | 0.8901 | |
| | 0.0153 | 95.0 | 1330 | 0.6312 | 0.8901 | |
| | 0.0153 | 96.0 | 1344 | 0.6310 | 0.8901 | |
| | 0.0153 | 97.0 | 1358 | 0.6305 | 0.8901 | |
| | 0.0153 | 98.0 | 1372 | 0.6306 | 0.8901 | |
| | 0.0153 | 99.0 | 1386 | 0.6307 | 0.8901 | |
| | 0.0153 | 100.0 | 1400 | 0.6307 | 0.8901 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.37.2 |
| - Pytorch 2.3.1 |
| - Datasets 2.19.1 |
| - Tokenizers 0.15.1 |
| |
