massive_indo
This model is a fine-tuned version of xxxxxxxxx on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.4772
- F1: 0.9465
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
4.5227 | 0.7 | 100 | 4.4260 | 0.0998 |
3.9734 | 1.41 | 200 | 3.9864 | 0.2616 |
3.6121 | 2.11 | 300 | 3.5977 | 0.3561 |
3.2481 | 2.82 | 400 | 3.2366 | 0.4929 |
2.9212 | 3.52 | 500 | 2.9196 | 0.5677 |
2.5236 | 4.23 | 600 | 2.6016 | 0.6625 |
2.3089 | 4.93 | 700 | 2.3252 | 0.7196 |
2.0311 | 5.63 | 800 | 2.0840 | 0.7740 |
1.793 | 6.34 | 900 | 1.8612 | 0.8168 |
1.5913 | 7.04 | 1000 | 1.6588 | 0.8524 |
1.4071 | 7.75 | 1100 | 1.4833 | 0.8781 |
1.2169 | 8.45 | 1200 | 1.3214 | 0.8806 |
1.1085 | 9.15 | 1300 | 1.2012 | 0.8983 |
0.9752 | 9.86 | 1400 | 1.0659 | 0.9145 |
0.8891 | 10.56 | 1500 | 0.9672 | 0.9165 |
0.7205 | 11.27 | 1600 | 0.8726 | 0.9225 |
0.6869 | 11.97 | 1700 | 0.8065 | 0.9320 |
0.5818 | 12.68 | 1800 | 0.7458 | 0.9367 |
0.5437 | 13.38 | 1900 | 0.6843 | 0.9374 |
0.4759 | 14.08 | 2000 | 0.6411 | 0.9357 |
0.4674 | 14.79 | 2100 | 0.6010 | 0.9388 |
0.4305 | 15.49 | 2200 | 0.5682 | 0.9427 |
0.3862 | 16.2 | 2300 | 0.5369 | 0.9424 |
0.3564 | 16.9 | 2400 | 0.5208 | 0.9412 |
0.3292 | 17.61 | 2500 | 0.5022 | 0.9424 |
0.3237 | 18.31 | 2600 | 0.4903 | 0.9450 |
0.3187 | 19.01 | 2700 | 0.4807 | 0.9460 |
0.317 | 19.72 | 2800 | 0.4772 | 0.9465 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3
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