metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-glue_cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
split: validation
args: cola
metrics:
- name: Accuracy
type: accuracy
value: 0.7957813998082455
- name: F1
type: f1
value: 0.7879207589996179
- name: Matthews Correlation
type: matthews_correlation
value: 0.4976864382248319
distilbert-base-uncased-finetuned-glue_cola
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5604
- Accuracy: 0.7958
- F1: 0.7879
- Matthews Correlation: 0.4977
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Matthews Correlation |
|---|---|---|---|---|---|---|
| 0.5632 | 1.0 | 535 | 0.4971 | 0.7603 | 0.7576 | 0.4273 |
| 0.4157 | 2.0 | 1070 | 0.4898 | 0.8015 | 0.7870 | 0.5051 |
| 0.2571 | 3.0 | 1605 | 0.5604 | 0.7958 | 0.7879 | 0.4977 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0