metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tiny-bert-sst2-mobilebert-distillation
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: sst2
split: train
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.8394495412844036
tiny-bert-sst2-mobilebert-distillation
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.2829
- Accuracy: 0.8394
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: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3094 | 1.0 | 4210 | 1.3514 | 0.8165 |
| 0.7514 | 2.0 | 8420 | 1.2829 | 0.8394 |
| 0.5799 | 3.0 | 12630 | 1.4556 | 0.8349 |
| 0.4909 | 4.0 | 16840 | 1.7050 | 0.8268 |
| 0.4312 | 5.0 | 21050 | 1.6662 | 0.8245 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1