metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: training-7
results: []
training-7
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0602
- Accuracy: 0.9878
- Precision: 0.9909
- Recall: 0.9842
- F1: 0.9875
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: 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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.5 | 131 | 0.0592 | 0.9856 | 0.9954 | 0.9752 | 0.9852 |
| No log | 1.0 | 262 | 0.0695 | 0.9789 | 0.9977 | 0.9594 | 0.9781 |
| 0.1477 | 1.49 | 393 | 0.0648 | 0.9822 | 0.9977 | 0.9661 | 0.9817 |
| 0.1477 | 1.99 | 524 | 0.0657 | 0.9833 | 0.9954 | 0.9707 | 0.9829 |
| 0.0555 | 2.49 | 655 | 0.0611 | 0.9856 | 0.9954 | 0.9752 | 0.9852 |
| 0.0555 | 2.99 | 786 | 0.0599 | 0.9889 | 0.9932 | 0.9842 | 0.9887 |
| 0.0243 | 3.49 | 917 | 0.0574 | 0.9878 | 0.9909 | 0.9842 | 0.9875 |
| 0.0243 | 3.98 | 1048 | 0.0602 | 0.9878 | 0.9909 | 0.9842 | 0.9875 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.2.0.dev20230913+cu121
- Tokenizers 0.13.3