metadata
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-cased
results: []
distilbert-base-cased
This model is a fine-tuned version of distilbert/distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0910
- Precision: 0.7563
- Recall: 0.7659
- F1: 0.7610
- Accuracy: 0.9763
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.151 | 1.0 | 784 | 0.0946 | 0.6986 | 0.7443 | 0.7207 | 0.9711 |
0.0391 | 2.0 | 1568 | 0.0859 | 0.7446 | 0.7678 | 0.7560 | 0.9750 |
0.0239 | 3.0 | 2352 | 0.0910 | 0.7563 | 0.7659 | 0.7610 | 0.9763 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2