|
|
--- |
|
|
library_name: transformers |
|
|
base_model: nreimers/BERT-Tiny_L-2_H-128_A-2 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: bert_tiny_trained |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# bert_tiny_trained |
|
|
|
|
|
This model is a fine-tuned version of [nreimers/BERT-Tiny_L-2_H-128_A-2](https://huggingface.co/nreimers/BERT-Tiny_L-2_H-128_A-2) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.5820 |
|
|
|
|
|
## 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: 8 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 50 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:-----:|:----:|:---------------:| |
|
|
| No log | 1.0 | 11 | 1.3285 | |
|
|
| No log | 2.0 | 22 | 1.3144 | |
|
|
| No log | 3.0 | 33 | 1.2977 | |
|
|
| No log | 4.0 | 44 | 1.2683 | |
|
|
| No log | 5.0 | 55 | 1.2476 | |
|
|
| No log | 6.0 | 66 | 1.2256 | |
|
|
| No log | 7.0 | 77 | 1.1961 | |
|
|
| No log | 8.0 | 88 | 1.1853 | |
|
|
| No log | 9.0 | 99 | 1.1625 | |
|
|
| No log | 10.0 | 110 | 1.1284 | |
|
|
| No log | 11.0 | 121 | 1.1036 | |
|
|
| No log | 12.0 | 132 | 1.0812 | |
|
|
| No log | 13.0 | 143 | 1.0573 | |
|
|
| No log | 14.0 | 154 | 1.0323 | |
|
|
| No log | 15.0 | 165 | 1.0092 | |
|
|
| No log | 16.0 | 176 | 0.9913 | |
|
|
| No log | 17.0 | 187 | 0.9725 | |
|
|
| No log | 18.0 | 198 | 0.9492 | |
|
|
| No log | 19.0 | 209 | 0.9269 | |
|
|
| No log | 20.0 | 220 | 0.9061 | |
|
|
| No log | 21.0 | 231 | 0.8869 | |
|
|
| No log | 22.0 | 242 | 0.8719 | |
|
|
| No log | 23.0 | 253 | 0.8521 | |
|
|
| No log | 24.0 | 264 | 0.8357 | |
|
|
| No log | 25.0 | 275 | 0.8169 | |
|
|
| No log | 26.0 | 286 | 0.8026 | |
|
|
| No log | 27.0 | 297 | 0.7936 | |
|
|
| No log | 28.0 | 308 | 0.7783 | |
|
|
| No log | 29.0 | 319 | 0.7677 | |
|
|
| No log | 30.0 | 330 | 0.7577 | |
|
|
| No log | 31.0 | 341 | 0.7516 | |
|
|
| No log | 32.0 | 352 | 0.7431 | |
|
|
| No log | 33.0 | 363 | 0.7355 | |
|
|
| No log | 34.0 | 374 | 0.7287 | |
|
|
| No log | 35.0 | 385 | 0.7220 | |
|
|
| No log | 36.0 | 396 | 0.7154 | |
|
|
| No log | 37.0 | 407 | 0.7119 | |
|
|
| No log | 38.0 | 418 | 0.7073 | |
|
|
| No log | 39.0 | 429 | 0.7025 | |
|
|
| No log | 40.0 | 440 | 0.6976 | |
|
|
| No log | 41.0 | 451 | 0.6931 | |
|
|
| No log | 42.0 | 462 | 0.6890 | |
|
|
| No log | 43.0 | 473 | 0.6859 | |
|
|
| No log | 44.0 | 484 | 0.6830 | |
|
|
| No log | 45.0 | 495 | 0.6807 | |
|
|
| 0.7544 | 46.0 | 506 | 0.6785 | |
|
|
| 0.7544 | 47.0 | 517 | 0.6774 | |
|
|
| 0.7544 | 48.0 | 528 | 0.6769 | |
|
|
| 0.7544 | 49.0 | 539 | 0.6768 | |
|
|
| 0.7544 | 50.0 | 550 | 0.6767 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.48.3 |
|
|
- Pytorch 2.5.1+cu124 |
|
|
- Datasets 3.3.2 |
|
|
- Tokenizers 0.21.0 |
|
|
|
