metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-finetuned-autext23
results: []
bert-base-uncased-finetuned-autext23
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: 0.7841
- Accuracy: 0.8924
- F1: 0.8916
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 1481 | 0.3827 | 0.8562 | 0.8539 |
| 0.2087 | 2.0 | 2962 | 0.4941 | 0.8861 | 0.8850 |
| 0.2087 | 3.0 | 4443 | 0.6297 | 0.8894 | 0.8885 |
| 0.0383 | 4.0 | 5924 | 0.8646 | 0.8669 | 0.8650 |
| 0.0383 | 5.0 | 7405 | 0.7841 | 0.8924 | 0.8916 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1