kaytoo2022/bert_test
By kaytoo2022 · ↓ 6 · ♥ 0 · Updated 2024-07-27
What's in this repo
This page lists the files in kaytoo2022/bert_test, including model.onnx, model_quantized.onnx.
- 2 ONNX models (.onnx files)
- 11 files, including 5 .json, 2 .onnx, 1 .md, 1 .h5, 1 .txt
- Last updated 2024-07-27
ONNX files
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
kaytoo2022/bert_test
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.8492
- Validation Loss: 2.0764
- Epoch: 2
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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 500, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 1.8457 | 2.0764 | 0 |
| 1.8353 | 2.0764 | 1 |
| 1.8492 | 2.0764 | 2 |
Framework versions
- Transformers 4.42.4
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1
Model info
Created: 2024-07-27
Updated: 2024-07-27
View on Hugging Face