tarekziade/topic_classification
By tarekziade · ↓ 5 · ♥ 0 · Updated 2023-12-19
What's in this repo
This page lists the files in tarekziade/topic_classification, including model.onnx, model_quantized.onnx.
- 2 ONNX models (.onnx files)
- 17 files, including 10 .json, 2 .onnx, 2 .txt, 1 .md, 1 .h5
- Last updated 2023-12-19
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
topic_classification_04
This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.8325
- Train Sparse Categorical Accuracy: 0.7237
- Epoch: 9
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', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Sparse Categorical Accuracy | Epoch |
|---|---|---|
| 1.0735 | 0.6503 | 0 |
| 0.9742 | 0.6799 | 1 |
| 0.9424 | 0.6900 | 2 |
| 0.9199 | 0.6970 | 3 |
| 0.9016 | 0.7026 | 4 |
| 0.8853 | 0.7073 | 5 |
| 0.8707 | 0.7120 | 6 |
| 0.8578 | 0.7160 | 7 |
| 0.8448 | 0.7199 | 8 |
| 0.8325 | 0.7237 | 9 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.9.1
- Datasets 2.3.2
- Tokenizers 0.12.1
Model info
Created: 2023-12-19
Updated: 2023-12-19
View on Hugging Face