metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased-finetuned_ADEs_SonatafyAI
results: []
bert-base-cased-finetuned_ADEs_SonatafyAI
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: 0.3543
- Precision: 0.3857
- Recall: 0.4776
- F1: 0.4268
- Accuracy: 0.8554
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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5644 | 1.0 | 640 | 0.4536 | 0.2717 | 0.3148 | 0.2916 | 0.8285 |
| 0.4695 | 2.0 | 1280 | 0.3977 | 0.3292 | 0.4109 | 0.3656 | 0.8462 |
| 0.4253 | 3.0 | 1920 | 0.3717 | 0.3653 | 0.4536 | 0.4047 | 0.8509 |
| 0.3872 | 4.0 | 2560 | 0.3578 | 0.3747 | 0.4623 | 0.4139 | 0.8544 |
| 0.3758 | 5.0 | 3200 | 0.3543 | 0.3857 | 0.4776 | 0.4268 | 0.8554 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1