metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_with_preprocessing_grid_search
results: []
BERT_with_preprocessing_grid_search
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: 0.8335
- Precision: 0.8310
- Recall: 0.8213
- F1: 0.8256
- Accuracy: 0.8640
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 255 | 0.6597 | 0.7225 | 0.7990 | 0.7429 | 0.7968 |
| 0.8033 | 2.0 | 510 | 0.5609 | 0.8155 | 0.8378 | 0.8247 | 0.8596 |
| 0.8033 | 3.0 | 765 | 0.5589 | 0.8119 | 0.8388 | 0.8231 | 0.8591 |
| 0.2454 | 4.0 | 1020 | 0.6598 | 0.8314 | 0.8273 | 0.8279 | 0.8625 |
| 0.2454 | 5.0 | 1275 | 0.6541 | 0.8103 | 0.8393 | 0.8229 | 0.8625 |
| 0.1332 | 6.0 | 1530 | 0.8259 | 0.8424 | 0.8213 | 0.8304 | 0.8665 |
| 0.1332 | 7.0 | 1785 | 0.7644 | 0.8298 | 0.8335 | 0.8312 | 0.8650 |
| 0.0907 | 8.0 | 2040 | 0.7939 | 0.8298 | 0.8255 | 0.8274 | 0.8660 |
| 0.0907 | 9.0 | 2295 | 0.8244 | 0.8310 | 0.8207 | 0.8255 | 0.8655 |
| 0.061 | 10.0 | 2550 | 0.8335 | 0.8310 | 0.8213 | 0.8256 | 0.8640 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3