metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
results: []
results
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1696
- Accuracy: 0.9308
- Class 0 Precision: 0.9947
- Class 0 Recall: 0.9319
- Class 0 F1: 0.9623
- Class 0 Support: 132570
- Class 1 Precision: 0.4316
- Class 1 Recall: 0.9118
- Class 1 F1: 0.5859
- Class 1 Support: 7517
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Class 0 Precision | Class 0 Recall | Class 0 F1 | Class 0 Support | Class 1 Precision | Class 1 Recall | Class 1 F1 | Class 1 Support |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2116 | 0.9998 | 2830 | 0.1709 | 0.9437 | 0.9334 | 0.9671 | 0.9500 | 6265 | 0.9574 | 0.9146 | 0.9355 | 5058 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1