metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: final_model
results: []
final_model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2616
- Accuracy: 0.9177
- Precision: 0.9289
- Recall: 0.9768
- F1: 0.9522
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 347 | 0.2485 | 0.9228 | 0.9224 | 0.9914 | 0.9557 |
| 0.2813 | 2.0 | 694 | 0.2604 | 0.9105 | 0.9193 | 0.9794 | 0.9484 |
| 0.2599 | 3.0 | 1041 | 0.2616 | 0.9177 | 0.9289 | 0.9768 | 0.9522 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1