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categorization-finetuned-20220721-164940-distilled-20220810-123313
This model is a fine-tuned version of carted-nlp/categorization-finetuned-20220721-164940 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0787
- Accuracy: 0.8416
- F1: 0.8396
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: 7e-06
- train_batch_size: 64
- eval_batch_size: 64
- seed: 314
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 15.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2976 | 0.56 | 2500 | 0.1441 | 0.7219 | 0.7071 |
| 0.1417 | 1.12 | 5000 | 0.1180 | 0.7719 | 0.7653 |
| 0.1236 | 1.69 | 7500 | 0.1076 | 0.7901 | 0.7854 |
| 0.1148 | 2.25 | 10000 | 0.1014 | 0.8015 | 0.7977 |
| 0.1092 | 2.81 | 12500 | 0.0972 | 0.8089 | 0.8052 |
| 0.1043 | 3.37 | 15000 | 0.0942 | 0.8135 | 0.8102 |
| 0.1013 | 3.94 | 17500 | 0.0916 | 0.8181 | 0.8147 |
| 0.0985 | 4.5 | 20000 | 0.0897 | 0.8219 | 0.8190 |
| 0.0962 | 5.06 | 22500 | 0.0881 | 0.8241 | 0.8215 |
| 0.0945 | 5.62 | 25000 | 0.0866 | 0.8270 | 0.8246 |
| 0.0928 | 6.19 | 27500 | 0.0857 | 0.8286 | 0.8262 |
| 0.0912 | 6.75 | 30000 | 0.0843 | 0.8310 | 0.8286 |
| 0.0901 | 7.31 | 32500 | 0.0836 | 0.8321 | 0.8299 |
| 0.0887 | 7.87 | 35000 | 0.0827 | 0.8339 | 0.8315 |
| 0.0879 | 8.43 | 37500 | 0.0821 | 0.8350 | 0.8329 |
| 0.0875 | 9.0 | 40000 | 0.0814 | 0.8362 | 0.8342 |
| 0.0865 | 9.56 | 42500 | 0.0811 | 0.8370 | 0.8348 |
| 0.0855 | 10.12 | 45000 | 0.0806 | 0.8375 | 0.8355 |
| 0.0853 | 10.68 | 47500 | 0.0798 | 0.8386 | 0.8367 |
| 0.0845 | 11.25 | 50000 | 0.0799 | 0.8392 | 0.8372 |
| 0.0844 | 11.81 | 52500 | 0.0793 | 0.8401 | 0.8383 |
| 0.0838 | 12.37 | 55000 | 0.0793 | 0.8402 | 0.8381 |
| 0.0834 | 12.93 | 57500 | 0.0790 | 0.8410 | 0.8390 |
| 0.0832 | 13.5 | 60000 | 0.0788 | 0.8414 | 0.8394 |
| 0.083 | 14.06 | 62500 | 0.0787 | 0.8415 | 0.8395 |
| 0.0828 | 14.62 | 65000 | 0.0787 | 0.8416 | 0.8396 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.11.6
