slac-taste
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1289
- Accuracy: 0.9076
- F1 Macro: 0.8815
- Precision Macro: 0.8776
- Recall Macro: 0.8857
- Total Tf: [1454, 148, 1454, 148]
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 212
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Total Tf |
|---|---|---|---|---|---|---|---|---|
| 0.4647 | 1.0 | 213 | 0.3426 | 0.9082 | 0.8894 | 0.8698 | 0.9217 | [1455, 147, 1455, 147] |
| 0.4011 | 2.0 | 426 | 0.3131 | 0.9238 | 0.9051 | 0.8917 | 0.9222 | [1480, 122, 1480, 122] |
| 0.2826 | 3.0 | 639 | 0.3667 | 0.9101 | 0.8899 | 0.8731 | 0.9144 | [1458, 144, 1458, 144] |
| 0.2055 | 4.0 | 852 | 0.4153 | 0.9164 | 0.8953 | 0.8834 | 0.9101 | [1468, 134, 1468, 134] |
| 0.1422 | 5.0 | 1065 | 0.4790 | 0.9151 | 0.8922 | 0.8847 | 0.9008 | [1466, 136, 1466, 136] |
| 0.1222 | 6.0 | 1278 | 0.6584 | 0.9164 | 0.8932 | 0.8876 | 0.8993 | [1468, 134, 1468, 134] |
| 0.0732 | 7.0 | 1491 | 0.7369 | 0.9020 | 0.8769 | 0.8666 | 0.8896 | [1445, 157, 1445, 157] |
| 0.0567 | 8.0 | 1704 | 0.8350 | 0.9107 | 0.8859 | 0.8807 | 0.8916 | [1459, 143, 1459, 143] |
| 0.0377 | 9.0 | 1917 | 0.8175 | 0.9120 | 0.8885 | 0.8804 | 0.8979 | [1461, 141, 1461, 141] |
| 0.0358 | 10.0 | 2130 | 0.9032 | 0.9107 | 0.8866 | 0.8794 | 0.8947 | [1459, 143, 1459, 143] |
| 0.0326 | 11.0 | 2343 | 0.9523 | 0.9039 | 0.8794 | 0.8687 | 0.8924 | [1448, 154, 1448, 154] |
| 0.011 | 12.0 | 2556 | 1.1113 | 0.9082 | 0.8817 | 0.8797 | 0.8838 | [1455, 147, 1455, 147] |
| 0.0159 | 13.0 | 2769 | 1.1049 | 0.9064 | 0.8810 | 0.8741 | 0.8887 | [1452, 150, 1452, 150] |
| 0.0191 | 14.0 | 2982 | 1.1846 | 0.9101 | 0.8831 | 0.8843 | 0.8819 | [1458, 144, 1458, 144] |
| 0.0095 | 15.0 | 3195 | 1.1289 | 0.9076 | 0.8815 | 0.8776 | 0.8857 | [1454, 148, 1454, 148] |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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