metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: insertion-prop05-vocab
results: []
insertion-prop05-vocab
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: 0.0209
- Precision: 0.9815
- Recall: 0.9787
- F1: 0.9801
- Accuracy: 0.9929
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0687 | 0.32 | 500 | 0.0275 | 0.9770 | 0.9694 | 0.9732 | 0.9904 |
| 0.0327 | 0.64 | 1000 | 0.0221 | 0.9791 | 0.9783 | 0.9787 | 0.9924 |
| 0.0289 | 0.96 | 1500 | 0.0209 | 0.9815 | 0.9787 | 0.9801 | 0.9929 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2