|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert-mini-sst2-distilled |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: glue |
|
type: glue |
|
args: sst2 |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.856651376146789 |
|
--- |
|
|
|
<!-- 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-mini-sst2-distilled |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the glue dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1792 |
|
- Accuracy: 0.8567 |
|
|
|
## 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: 0.00021185586235152412 |
|
- train_batch_size: 1024 |
|
- eval_batch_size: 1024 |
|
- seed: 33 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 8 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.1552 | 1.0 | 66 | 1.4847 | 0.8349 | |
|
| 0.8451 | 2.0 | 132 | 1.3495 | 0.8624 | |
|
| 0.5864 | 3.0 | 198 | 1.2257 | 0.8532 | |
|
| 0.4553 | 4.0 | 264 | 1.2571 | 0.8544 | |
|
| 0.3708 | 5.0 | 330 | 1.2132 | 0.8658 | |
|
| 0.3086 | 6.0 | 396 | 1.2370 | 0.8589 | |
|
| 0.2701 | 7.0 | 462 | 1.1900 | 0.8635 | |
|
| 0.246 | 8.0 | 528 | 1.1792 | 0.8567 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.12.3 |
|
- Pytorch 1.9.1 |
|
- Datasets 1.15.1 |
|
- Tokenizers 0.10.3 |
|
|
