metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned-bert-mrpc
results: []
finetuned-bert-mrpc
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4808
- Accuracy: 0.8284
- F1: 0.8793
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
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.5496 | 1.0 | 230 | 0.4244 | 0.8137 | 0.8729 |
0.3172 | 2.0 | 460 | 0.3921 | 0.8260 | 0.8765 |
0.1431 | 3.0 | 690 | 0.4808 | 0.8284 | 0.8793 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1