metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
- matthews_correlation
model-index:
- name: bert-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: 0.8293384467881112
- name: F1
type: f1
value: 0.820234272230632
- name: Matthews Correlation
type: matthews_correlation
value: 0.5806473000395166
bert-base-uncased-finetuned-glue_cola
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6466
- Accuracy: 0.8293
- F1: 0.8202
- Matthews Correlation: 0.5806
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 |
---|---|---|---|---|---|---|
0.5418 | 1.0 | 535 | 0.4594 | 0.8006 | 0.7836 | 0.5019 |
0.3635 | 2.0 | 1070 | 0.4437 | 0.8217 | 0.8084 | 0.5600 |
0.2019 | 3.0 | 1605 | 0.6466 | 0.8293 | 0.8202 | 0.5806 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0