metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: bert-base-cased
model-index:
- name: bertBasev2
results: []
bertBasev2
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0328
- Precision: 0.9539
- Recall: 0.9707
- F1: 0.9622
- Accuracy: 0.9911
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: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.2004 | 1.0 | 1012 | 0.9504 | 0.2620 | 0.3519 | 0.3004 | 0.6856 |
| 1.0265 | 2.0 | 2024 | 0.6205 | 0.4356 | 0.5161 | 0.4725 | 0.7956 |
| 0.6895 | 3.0 | 3036 | 0.3269 | 0.6694 | 0.7302 | 0.6985 | 0.9044 |
| 0.44 | 4.0 | 4048 | 0.1325 | 0.8356 | 0.9091 | 0.8708 | 0.9667 |
| 0.2585 | 5.0 | 5060 | 0.0717 | 0.9259 | 0.9531 | 0.9393 | 0.9844 |
| 0.1722 | 6.0 | 6072 | 0.0382 | 0.9480 | 0.9619 | 0.9549 | 0.99 |
| 0.0919 | 7.0 | 7084 | 0.0328 | 0.9539 | 0.9707 | 0.9622 | 0.9911 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1