metadata
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: our_awesome_BERT_model
results: []
our_awesome_BERT_model
This model is a fine-tuned version of distilbert/distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0567
- Precision: 0.7594
- Recall: 0.7909
- F1: 0.7748
- Accuracy: 0.9825
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1072 | 1.0 | 784 | 0.0602 | 0.7686 | 0.7360 | 0.7520 | 0.9807 |
| 0.0271 | 2.0 | 1568 | 0.0567 | 0.7594 | 0.7909 | 0.7748 | 0.9825 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.0+cpu
- Datasets 2.19.0
- Tokenizers 0.15.2