metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-ft-news
results: []
bert-base-uncased-ft-news
This model is a fine-tuned version of bert-base-uncased on the news dataset. It achieves the following results on the evaluation set:
- Loss: 0.4300
- Accuracy: 0.9
- F1: 0.8783
and flowing results on the testing set:
- Accuracy: 0.8954
- F1: 0.8784
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4196 | 0.37 | 120 | 0.3051 | 0.8875 | 0.8566 |
| 0.3101 | 0.75 | 240 | 0.2979 | 0.8953 | 0.8743 |
| 0.2693 | 1.12 | 360 | 0.3162 | 0.9016 | 0.8831 |
| 0.2078 | 1.5 | 480 | 0.3298 | 0.8984 | 0.8767 |
| 0.1725 | 1.87 | 600 | 0.3801 | 0.9047 | 0.8851 |
| 0.1369 | 2.24 | 720 | 0.3901 | 0.8938 | 0.8677 |
| 0.1101 | 2.62 | 840 | 0.4160 | 0.9016 | 0.8805 |
| 0.1019 | 2.99 | 960 | 0.4300 | 0.9 | 0.8783 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2