metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentence_classfication_test
results: []
sentence_classfication_test
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: 0.7145
- Accuracy: 0.7692
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 33 | 0.7357 | 0.6385 |
| No log | 2.0 | 66 | 0.6801 | 0.6615 |
| No log | 3.0 | 99 | 0.6015 | 0.7923 |
| No log | 4.0 | 132 | 0.6450 | 0.7615 |
| No log | 5.0 | 165 | 0.7437 | 0.7 |
| No log | 6.0 | 198 | 0.5748 | 0.7692 |
| No log | 7.0 | 231 | 0.8001 | 0.7077 |
| No log | 8.0 | 264 | 0.6965 | 0.7615 |
| No log | 9.0 | 297 | 0.7052 | 0.7538 |
| No log | 10.0 | 330 | 0.7145 | 0.7692 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3