metadata
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tiny-bert-sst2-distilled
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: 0.819954128440367
tiny-bert-sst2-distilled
This model was trained from scratch on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6749
- Accuracy: 0.8200
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: 6e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 33
- 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 |
|---|---|---|---|---|
| 0.1125 | 1.0 | 3 | 0.6731 | 0.8177 |
| 0.0984 | 2.0 | 6 | 0.6756 | 0.8188 |
| 0.1273 | 3.0 | 9 | 0.6754 | 0.8177 |
| 0.0758 | 4.0 | 12 | 0.6751 | 0.8188 |
| 0.1188 | 5.0 | 15 | 0.6754 | 0.8188 |
| 0.0936 | 6.0 | 18 | 0.6749 | 0.8200 |
| 0.0781 | 7.0 | 21 | 0.6748 | 0.8200 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0