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categorization-finetuned-20220721-164940-pruned-20220803-123018
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: 0.5476
- Accuracy: 0.8558
- F1: 0.8539
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: 48
- eval_batch_size: 48
- seed: 314
- gradient_accumulation_steps: 6
- total_train_batch_size: 288
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.3421 | 0.51 | 2000 | 0.4324 | 0.8871 | 0.8864 |
| 0.3435 | 1.01 | 4000 | 0.4276 | 0.8885 | 0.8878 |
| 0.327 | 1.52 | 6000 | 0.4300 | 0.8891 | 0.8884 |
| 0.3299 | 2.02 | 8000 | 0.4266 | 0.8891 | 0.8885 |
| 0.3217 | 2.53 | 10000 | 0.4303 | 0.8881 | 0.8873 |
| 0.3347 | 3.04 | 12000 | 0.4291 | 0.8885 | 0.8879 |
| 0.3307 | 3.54 | 14000 | 0.4334 | 0.8873 | 0.8867 |
| 0.3537 | 4.05 | 16000 | 0.4340 | 0.8850 | 0.8844 |
| 0.3659 | 4.56 | 18000 | 0.4426 | 0.8828 | 0.8819 |
| 0.3933 | 5.06 | 20000 | 0.4485 | 0.8805 | 0.8796 |
| 0.4117 | 5.57 | 22000 | 0.4553 | 0.8779 | 0.8768 |
| 0.4501 | 6.07 | 24000 | 0.4734 | 0.8734 | 0.8725 |
| 0.4848 | 6.58 | 26000 | 0.4895 | 0.8690 | 0.8678 |
| 0.5182 | 7.09 | 28000 | 0.5137 | 0.8634 | 0.8617 |
| 0.54 | 7.59 | 30000 | 0.5165 | 0.8625 | 0.8610 |
| 0.5582 | 8.1 | 32000 | 0.5312 | 0.8591 | 0.8572 |
| 0.5728 | 8.61 | 34000 | 0.5382 | 0.8574 | 0.8556 |
| 0.5883 | 9.11 | 36000 | 0.5514 | 0.8553 | 0.8534 |
| 0.5942 | 9.62 | 38000 | 0.5563 | 0.8534 | 0.8512 |
| 0.6015 | 10.12 | 40000 | 0.5592 | 0.8536 | 0.8516 |
| 0.603 | 10.63 | 42000 | 0.5585 | 0.8533 | 0.8513 |
| 0.5972 | 11.14 | 44000 | 0.5585 | 0.8541 | 0.8520 |
| 0.5938 | 11.64 | 46000 | 0.5546 | 0.8548 | 0.8529 |
| 0.5882 | 12.15 | 48000 | 0.5515 | 0.8554 | 0.8535 |
| 0.5799 | 12.65 | 50000 | 0.5488 | 0.8561 | 0.8541 |
| 0.572 | 13.16 | 52000 | 0.5473 | 0.8566 | 0.8547 |
| 0.5718 | 13.67 | 54000 | 0.5468 | 0.8566 | 0.8547 |
| 0.5698 | 14.17 | 56000 | 0.5464 | 0.8566 | 0.8547 |
| 0.5696 | 14.68 | 58000 | 0.5464 | 0.8566 | 0.8547 |
Framework versions
- Transformers 4.18.0.dev0
- Pytorch 1.9.1+cu111
- Datasets 2.3.2
- Tokenizers 0.11.6
