metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: classify
results: []
classify
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: 0.5723
- Precision: 0.0
- Recall: 0.0
- F1 Binary: 0.0
- Accuracy: 0.7429
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 0
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Binary | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 0.7028 | 0.2437 | 0.7160 | 0.3636 | 0.3556 |
| 0.6 | 2.8181 | 1000 | 0.5779 | 0.0 | 0.0 | 0.0 | 0.7429 |
| 0.5522 | 5.6347 | 2000 | 0.5709 | 0.0 | 0.0 | 0.0 | 0.7429 |
| 0.5582 | 8.4513 | 3000 | 0.5709 | 0.0 | 0.0 | 0.0 | 0.7429 |
| 0.5791 | 11.2680 | 4000 | 0.5703 | 0.0 | 0.0 | 0.0 | 0.7429 |
| 0.5895 | 14.0846 | 5000 | 0.5701 | 0.0 | 0.0 | 0.0 | 0.7429 |
| 0.5629 | 16.9027 | 6000 | 0.5730 | 0.0 | 0.0 | 0.0 | 0.7429 |
| 0.5841 | 19.7193 | 7000 | 0.5723 | 0.0 | 0.0 | 0.0 | 0.7429 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.3.0
- Datasets 3.2.0
- Tokenizers 0.21.0