metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: bert-tiny-target-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
split: train
args: cola
metrics:
- name: Matthews Correlation
type: matthews_correlation
value: 0.14578167065086653
bert-tiny-target-cola
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: 0.6626
- Matthews Correlation: 0.1458
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| 0.6124 | 1.87 | 500 | 0.6192 | 0.0 |
| 0.6016 | 3.73 | 1000 | 0.6167 | 0.0 |
| 0.5838 | 5.6 | 1500 | 0.6166 | 0.0149 |
| 0.5555 | 7.46 | 2000 | 0.6344 | 0.0465 |
| 0.5272 | 9.33 | 2500 | 0.6542 | 0.1399 |
| 0.5058 | 11.19 | 3000 | 0.6626 | 0.1458 |
| 0.4791 | 13.06 | 3500 | 0.6868 | 0.1192 |
| 0.4577 | 14.93 | 4000 | 0.7215 | 0.1230 |
| 0.4425 | 16.79 | 4500 | 0.7322 | 0.1243 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2