metadata
license: apache-2.0
tags:
- classification
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
base_model: bert-base-uncased
model-index:
- name: test-trainer
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: glue
type: glue
config: mrpc
split: train
args: mrpc
metrics:
- type: accuracy
value: 0.8553921568627451
name: Accuracy
- type: f1
value: 0.9008403361344538
name: F1
test-trainer
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: 0.5655
- Accuracy: 0.8554
- F1: 0.9008
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 459 | 0.3654 | 0.8358 | 0.8843 |
| 0.5335 | 2.0 | 918 | 0.4351 | 0.8505 | 0.8982 |
| 0.3401 | 3.0 | 1377 | 0.5655 | 0.8554 | 0.9008 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2