CS505-Classifier-T4_predictLabel_a1_v3
This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0095
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: 32
- eval_batch_size: 8
- 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 |
---|---|---|---|
No log | 0.98 | 48 | 1.0278 |
No log | 1.96 | 96 | 0.5582 |
No log | 2.94 | 144 | 0.3632 |
No log | 3.92 | 192 | 0.2807 |
No log | 4.9 | 240 | 0.2237 |
No log | 5.88 | 288 | 0.1827 |
No log | 6.86 | 336 | 0.1383 |
No log | 7.84 | 384 | 0.1124 |
No log | 8.82 | 432 | 0.0880 |
No log | 9.8 | 480 | 0.0866 |
0.4209 | 10.78 | 528 | 0.0562 |
0.4209 | 11.76 | 576 | 0.0444 |
0.4209 | 12.73 | 624 | 0.0399 |
0.4209 | 13.71 | 672 | 0.0301 |
0.4209 | 14.69 | 720 | 0.0262 |
0.4209 | 15.67 | 768 | 0.0245 |
0.4209 | 16.65 | 816 | 0.0216 |
0.4209 | 17.63 | 864 | 0.0207 |
0.4209 | 18.61 | 912 | 0.0179 |
0.4209 | 19.59 | 960 | 0.0170 |
0.0435 | 20.57 | 1008 | 0.0162 |
0.0435 | 21.55 | 1056 | 0.0130 |
0.0435 | 22.53 | 1104 | 0.0122 |
0.0435 | 23.51 | 1152 | 0.0120 |
0.0435 | 24.49 | 1200 | 0.0107 |
0.0435 | 25.47 | 1248 | 0.0102 |
0.0435 | 26.45 | 1296 | 0.0098 |
0.0435 | 27.43 | 1344 | 0.0096 |
0.0435 | 28.41 | 1392 | 0.0097 |
0.0435 | 29.39 | 1440 | 0.0095 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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