metadata
base_model: huawei-noah/TinyBERT_General_4L_312D
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Tiny_Bert_Cupstone
results: []
Tiny_Bert_Cupstone
This model is a fine-tuned version of huawei-noah/TinyBERT_General_4L_312D on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3333
- Accuracy: 0.8550
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: 8
- eval_batch_size: 8
- 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 | Accuracy |
|---|---|---|---|---|
| 0.524 | 0.2 | 500 | 0.4015 | 0.8318 |
| 0.4268 | 0.4 | 1000 | 0.4274 | 0.8279 |
| 0.39 | 0.6 | 1500 | 0.3743 | 0.8502 |
| 0.3674 | 0.8 | 2000 | 0.3333 | 0.8550 |
| 0.3687 | 1.0 | 2500 | 0.3836 | 0.8585 |
| 0.3489 | 1.2 | 3000 | 0.3927 | 0.8548 |
| 0.3193 | 1.41 | 3500 | 0.3938 | 0.8669 |
| 0.3525 | 1.61 | 4000 | 0.3717 | 0.8753 |
| 0.3327 | 1.81 | 4500 | 0.4589 | 0.8573 |
| 0.3276 | 2.01 | 5000 | 0.3676 | 0.8791 |
| 0.285 | 2.21 | 5500 | 0.4196 | 0.8811 |
| 0.2757 | 2.41 | 6000 | 0.3973 | 0.8777 |
| 0.277 | 2.61 | 6500 | 0.4198 | 0.8805 |
| 0.2834 | 2.81 | 7000 | 0.4955 | 0.8739 |
| 0.338 | 3.01 | 7500 | 0.4383 | 0.8844 |
| 0.2499 | 3.21 | 8000 | 0.4745 | 0.8785 |
| 0.2405 | 3.41 | 8500 | 0.4794 | 0.8854 |
| 0.2648 | 3.61 | 9000 | 0.4576 | 0.8844 |
| 0.2379 | 3.81 | 9500 | 0.4395 | 0.8886 |
| 0.2343 | 4.01 | 10000 | 0.5088 | 0.8791 |
| 0.2011 | 4.22 | 10500 | 0.5272 | 0.8781 |
| 0.2198 | 4.42 | 11000 | 0.5235 | 0.8765 |
| 0.2343 | 4.62 | 11500 | 0.5019 | 0.8844 |
| 0.194 | 4.82 | 12000 | 0.5227 | 0.8791 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1