|
--- |
|
license: apache-2.0 |
|
base_model: google/bert_uncased_L-2_H-128_A-2 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert_distillation_tiny |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: glue |
|
type: glue |
|
config: sst2 |
|
split: validation |
|
args: sst2 |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8256880733944955 |
|
--- |
|
|
|
<!-- 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_distillation_tiny |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the glue dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4274 |
|
- Accuracy: 0.8257 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 128 |
|
- eval_batch_size: 128 |
|
- seed: 2023 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 7 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.4139 | 1.0 | 527 | 0.4204 | 0.8096 | |
|
| 0.27 | 2.0 | 1054 | 0.4274 | 0.8257 | |
|
| 0.2226 | 3.0 | 1581 | 0.4899 | 0.8245 | |
|
| 0.1931 | 4.0 | 2108 | 0.4961 | 0.8222 | |
|
| 0.1732 | 5.0 | 2635 | 0.5302 | 0.8222 | |
|
| 0.1608 | 6.0 | 3162 | 0.5393 | 0.8234 | |
|
| 0.152 | 7.0 | 3689 | 0.5562 | 0.8177 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
