metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: fine-tuned-bert-base-uncased
results: []
fine-tuned-bert-base-uncased
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2400
- F1: 0.7987
- Roc Auc: 0.8779
- Accuracy: 0.5990
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.2624 | 1.0 | 2002 | 0.2666 | 0.6748 | 0.7869 | 0.4353 |
| 0.2129 | 2.0 | 4004 | 0.2405 | 0.7226 | 0.8141 | 0.4914 |
| 0.1541 | 3.0 | 6006 | 0.2436 | 0.7561 | 0.8450 | 0.5380 |
| 0.1197 | 4.0 | 8008 | 0.2352 | 0.7887 | 0.8704 | 0.5795 |
| 0.0897 | 5.0 | 10010 | 0.2400 | 0.7987 | 0.8779 | 0.5990 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2