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afx-grouping-model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0154
- Accuracy: 1.0
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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 6 | 0.9060 | 0.7674 |
| No log | 2.0 | 12 | 0.7408 | 0.7674 |
| No log | 3.0 | 18 | 0.6209 | 0.8023 |
| No log | 4.0 | 24 | 0.5090 | 0.8023 |
| No log | 5.0 | 30 | 0.4159 | 0.8488 |
| No log | 6.0 | 36 | 0.3407 | 0.8837 |
| No log | 7.0 | 42 | 0.2719 | 0.9535 |
| No log | 8.0 | 48 | 0.2218 | 0.9535 |
| No log | 9.0 | 54 | 0.1801 | 0.9535 |
| No log | 10.0 | 60 | 0.1476 | 0.9535 |
| No log | 11.0 | 66 | 0.1164 | 0.9767 |
| No log | 12.0 | 72 | 0.0937 | 0.9884 |
| No log | 13.0 | 78 | 0.0723 | 1.0 |
| No log | 14.0 | 84 | 0.0604 | 1.0 |
| No log | 15.0 | 90 | 0.0485 | 1.0 |
| No log | 16.0 | 96 | 0.0395 | 1.0 |
| No log | 17.0 | 102 | 0.0339 | 1.0 |
| No log | 18.0 | 108 | 0.0307 | 1.0 |
| No log | 19.0 | 114 | 0.0262 | 1.0 |
| No log | 20.0 | 120 | 0.0240 | 1.0 |
| No log | 21.0 | 126 | 0.0215 | 1.0 |
| No log | 22.0 | 132 | 0.0200 | 1.0 |
| No log | 23.0 | 138 | 0.0189 | 1.0 |
| No log | 24.0 | 144 | 0.0178 | 1.0 |
| No log | 25.0 | 150 | 0.0170 | 1.0 |
| No log | 26.0 | 156 | 0.0164 | 1.0 |
| No log | 27.0 | 162 | 0.0160 | 1.0 |
| No log | 28.0 | 168 | 0.0157 | 1.0 |
| No log | 29.0 | 174 | 0.0155 | 1.0 |
| No log | 30.0 | 180 | 0.0154 | 1.0 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3
