metadata
license: apache-2.0
base_model: bert-large-uncased-whole-word-masking
tags:
- generated_from_trainer
model-index:
- name: pictalk
results: []
pictalk
This model is a fine-tuned version of bert-large-uncased-whole-word-masking on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5286
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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.2507 | 1.0 | 25 | 2.7433 |
| 2.518 | 2.0 | 50 | 2.2772 |
| 2.323 | 3.0 | 75 | 2.0185 |
| 2.0883 | 4.0 | 100 | 1.9731 |
| 1.8835 | 5.0 | 125 | 1.9086 |
| 1.8641 | 6.0 | 150 | 1.7880 |
| 1.7244 | 7.0 | 175 | 1.7763 |
| 1.7395 | 8.0 | 200 | 1.7191 |
| 1.6834 | 9.0 | 225 | 1.6734 |
| 1.6631 | 10.0 | 250 | 1.6970 |
| 1.5764 | 11.0 | 275 | 1.6939 |
| 1.54 | 12.0 | 300 | 1.6576 |
| 1.5205 | 13.0 | 325 | 1.5530 |
| 1.4832 | 14.0 | 350 | 1.5448 |
| 1.4582 | 15.0 | 375 | 1.6000 |
| 1.418 | 16.0 | 400 | 1.5240 |
| 1.4152 | 17.0 | 425 | 1.5330 |
| 1.3529 | 18.0 | 450 | 1.5850 |
| 1.3886 | 19.0 | 475 | 1.4814 |
| 1.3268 | 20.0 | 500 | 1.6087 |
| 1.2914 | 21.0 | 525 | 1.5714 |
| 1.3431 | 22.0 | 550 | 1.4989 |
| 1.2838 | 23.0 | 575 | 1.5934 |
| 1.2943 | 24.0 | 600 | 1.4751 |
| 1.2704 | 25.0 | 625 | 1.5158 |
| 1.284 | 26.0 | 650 | 1.6148 |
| 1.2148 | 27.0 | 675 | 1.4828 |
| 1.2382 | 28.0 | 700 | 1.4890 |
| 1.1684 | 29.0 | 725 | 1.5531 |
| 1.2053 | 30.0 | 750 | 1.4755 |
| 1.1973 | 31.0 | 775 | 1.4426 |
| 1.2127 | 32.0 | 800 | 1.5464 |
| 1.1802 | 33.0 | 825 | 1.4410 |
| 1.1828 | 34.0 | 850 | 1.5026 |
| 1.1338 | 35.0 | 875 | 1.5691 |
| 1.11 | 36.0 | 900 | 1.5073 |
| 1.1456 | 37.0 | 925 | 1.5055 |
| 1.1253 | 38.0 | 950 | 1.5108 |
| 1.1214 | 39.0 | 975 | 1.4563 |
| 1.1654 | 40.0 | 1000 | 1.5881 |
| 1.0921 | 41.0 | 1025 | 1.4060 |
| 1.1087 | 42.0 | 1050 | 1.4952 |
| 1.0824 | 43.0 | 1075 | 1.5512 |
| 1.1127 | 44.0 | 1100 | 1.5481 |
| 1.0994 | 45.0 | 1125 | 1.5692 |
| 1.0579 | 46.0 | 1150 | 1.4802 |
| 1.1006 | 47.0 | 1175 | 1.5585 |
| 1.0692 | 48.0 | 1200 | 1.4303 |
| 1.1131 | 49.0 | 1225 | 1.5129 |
| 1.0943 | 50.0 | 1250 | 1.5286 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0