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: 0.5941
- F1: 0.2075
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
1.6114 | 0.18 | 4000 | 2.8696 | 0.0216 |
1.175 | 0.37 | 8000 | 2.4185 | 0.0298 |
1.0297 | 0.55 | 12000 | 2.2393 | 0.0265 |
0.9481 | 0.74 | 16000 | 2.0412 | 0.0359 |
0.907 | 0.92 | 20000 | 1.9175 | 0.0369 |
0.8091 | 1.11 | 24000 | 1.7551 | 0.0542 |
0.7541 | 1.29 | 28000 | 1.6911 | 0.0638 |
0.7476 | 1.48 | 32000 | 1.5999 | 0.0736 |
0.6812 | 1.66 | 36000 | 1.5595 | 0.0887 |
0.6615 | 1.85 | 40000 | 1.4151 | 0.1002 |
0.5681 | 2.03 | 44000 | 1.3710 | 0.1013 |
0.5088 | 2.22 | 48000 | 1.2370 | 0.1176 |
0.5355 | 2.4 | 52000 | 1.1219 | 0.1327 |
0.4965 | 2.59 | 56000 | 1.1772 | 0.1381 |
0.4671 | 2.77 | 60000 | 1.0597 | 0.1549 |
0.4902 | 2.95 | 64000 | 1.0120 | 0.1549 |
0.4143 | 3.14 | 68000 | 0.8947 | 0.1836 |
0.3805 | 3.32 | 72000 | 0.8788 | 0.1731 |
0.3766 | 3.51 | 76000 | 0.8115 | 0.1762 |
0.3691 | 3.69 | 80000 | 0.8016 | 0.1800 |
0.3698 | 3.88 | 84000 | 0.7637 | 0.1857 |
0.3368 | 4.06 | 88000 | 0.7051 | 0.1933 |
0.3267 | 4.25 | 92000 | 0.6571 | 0.1969 |
0.34 | 4.43 | 96000 | 0.6427 | 0.1980 |
0.2947 | 4.62 | 100000 | 0.6451 | 0.2029 |
0.3118 | 4.8 | 104000 | 0.6006 | 0.2018 |
0.2873 | 4.99 | 108000 | 0.5941 | 0.2075 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.0
- Downloads last month
- 8
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.