metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_without_preprocessing_grid_search
results: []
BERT_without_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: 0.6705
- Precision: 0.8452
- Recall: 0.8581
- F1: 0.8510
- Accuracy: 0.8818
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 | 257 | 0.5962 | 0.7414 | 0.8132 | 0.7626 | 0.8268 |
| 0.7597 | 2.0 | 514 | 0.5120 | 0.8170 | 0.8507 | 0.8292 | 0.8652 |
| 0.7597 | 3.0 | 771 | 0.4818 | 0.7975 | 0.8565 | 0.8202 | 0.8652 |
| 0.2391 | 4.0 | 1028 | 0.5223 | 0.8220 | 0.8613 | 0.8377 | 0.8652 |
| 0.2391 | 5.0 | 1285 | 0.5516 | 0.8172 | 0.8599 | 0.8347 | 0.8706 |
| 0.1316 | 6.0 | 1542 | 0.5747 | 0.8139 | 0.8593 | 0.8333 | 0.8710 |
| 0.1316 | 7.0 | 1799 | 0.6290 | 0.8332 | 0.8483 | 0.8386 | 0.8701 |
| 0.0773 | 8.0 | 2056 | 0.6089 | 0.8312 | 0.8620 | 0.8450 | 0.8764 |
| 0.0773 | 9.0 | 2313 | 0.6633 | 0.8384 | 0.8532 | 0.8448 | 0.8774 |
| 0.0633 | 10.0 | 2570 | 0.6705 | 0.8452 | 0.8581 | 0.8510 | 0.8818 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3