metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-training-3
results: []
distilbert-training-3
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0197
- Accuracy: 0.9956
- Precision: 1.0
- Recall: 0.9910
- F1: 0.9955
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: 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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 0.5 | 131 | 0.1115 | 0.97 | 0.9976 | 0.9413 | 0.9686 |
| No log | 1.0 | 262 | 0.0659 | 0.9844 | 1.0 | 0.9684 | 0.9839 |
| 0.1414 | 1.49 | 393 | 0.0632 | 0.9878 | 1.0 | 0.9752 | 0.9874 |
| 0.1414 | 1.99 | 524 | 0.0795 | 0.9822 | 1.0 | 0.9639 | 0.9816 |
| 0.0512 | 2.49 | 655 | 0.0542 | 0.9878 | 1.0 | 0.9752 | 0.9874 |
| 0.0512 | 2.99 | 786 | 0.0199 | 0.9944 | 1.0 | 0.9887 | 0.9943 |
| 0.0246 | 3.49 | 917 | 0.0202 | 0.9944 | 1.0 | 0.9887 | 0.9943 |
| 0.0246 | 3.98 | 1048 | 0.0197 | 0.9956 | 1.0 | 0.9910 | 0.9955 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.2.0.dev20230913+cu121
- Tokenizers 0.13.3