metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- recall
- precision
- f1
model-index:
- name: model1
results: []
model1
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: 0.0018
- Recall: 0.9997
- Precision: 0.9997
- F1: 0.9997
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1 |
|---|---|---|---|---|---|---|
| 0.0238 | 1.0 | 856 | 0.0024 | 0.9995 | 0.9995 | 0.9995 |
| 0.0013 | 2.0 | 1712 | 0.0018 | 0.9997 | 0.9997 | 0.9997 |
| 0.0006 | 3.0 | 2568 | 0.0019 | 0.9997 | 0.9997 | 0.9997 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2