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categorization-finetuned-20220721-164940-pruned-20220803-184651
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: 0.4673
- Accuracy: 0.8760
- F1: 0.8751
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: 1000
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.3404 | 0.51 | 2000 | 0.4329 | 0.8872 | 0.8865 |
| 0.3433 | 1.01 | 4000 | 0.4280 | 0.8883 | 0.8876 |
| 0.3281 | 1.52 | 6000 | 0.4302 | 0.8890 | 0.8883 |
| 0.331 | 2.02 | 8000 | 0.4265 | 0.8891 | 0.8885 |
| 0.3224 | 2.53 | 10000 | 0.4300 | 0.8881 | 0.8874 |
| 0.3361 | 3.04 | 12000 | 0.4291 | 0.8889 | 0.8882 |
| 0.3323 | 3.54 | 14000 | 0.4337 | 0.8878 | 0.8871 |
| 0.3556 | 4.05 | 16000 | 0.4345 | 0.8857 | 0.8851 |
| 0.3663 | 4.56 | 18000 | 0.4417 | 0.8836 | 0.8828 |
| 0.3902 | 5.06 | 20000 | 0.4555 | 0.8789 | 0.8781 |
| 0.4036 | 5.57 | 22000 | 0.4556 | 0.8788 | 0.8779 |
| 0.4305 | 6.07 | 24000 | 0.4697 | 0.8751 | 0.8742 |
| 0.4501 | 6.58 | 26000 | 0.4763 | 0.8738 | 0.8725 |
| 0.4733 | 7.09 | 28000 | 0.4857 | 0.8710 | 0.8700 |
| 0.4851 | 7.59 | 30000 | 0.4863 | 0.8705 | 0.8695 |
| 0.4846 | 8.1 | 32000 | 0.4849 | 0.8708 | 0.8698 |
| 0.4856 | 8.61 | 34000 | 0.4835 | 0.8707 | 0.8695 |
| 0.4774 | 9.11 | 36000 | 0.4797 | 0.8719 | 0.8708 |
| 0.4635 | 9.62 | 38000 | 0.4776 | 0.8728 | 0.8717 |
| 0.4561 | 10.12 | 40000 | 0.4746 | 0.8739 | 0.8729 |
| 0.4475 | 10.63 | 42000 | 0.4705 | 0.8749 | 0.8740 |
| 0.4413 | 11.14 | 44000 | 0.4691 | 0.8754 | 0.8744 |
| 0.4389 | 11.64 | 46000 | 0.4679 | 0.8760 | 0.8750 |
| 0.4361 | 12.15 | 48000 | 0.4677 | 0.8759 | 0.8749 |
| 0.4362 | 12.65 | 50000 | 0.4672 | 0.8763 | 0.8753 |
| 0.4309 | 13.16 | 52000 | 0.4671 | 0.8761 | 0.8751 |
| 0.4316 | 13.67 | 54000 | 0.4670 | 0.8764 | 0.8754 |
| 0.4321 | 14.17 | 56000 | 0.4668 | 0.8764 | 0.8755 |
| 0.4311 | 14.68 | 58000 | 0.4668 | 0.8764 | 0.8754 |
Framework versions
- Transformers 4.18.0.dev0
- Pytorch 1.9.1+cu111
- Datasets 2.3.2
- Tokenizers 0.11.6
