onnx-community/trained-gender-ONNX
By onnx-community · ↓ 5 · ♥ 0 · Updated 2025-11-11
What's in this repo
This page lists the files in onnx-community/trained-gender-ONNX, including model.onnx, model_bnb4.onnx, model_fp16.onnx and more.
- 8 ONNX models (.onnx files)
- 13 files, including 8 .onnx, 3 .json, 1 .md
- Last updated 2025-11-11
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/model.onnx | — | Download |
| onnx/model_bnb4.onnx | — | Download |
| onnx/model_fp16.onnx | — | Download |
| onnx/model_int8.onnx | — | Download |
| onnx/model_q4.onnx | — | Download |
| onnx/model_q4f16.onnx | — | Download |
| onnx/model_quantized.onnx | — | Download |
| onnx/model_uint8.onnx | — | Download |
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
trained-gender (ONNX)
This is an ONNX version of crangana/trained-gender. It was automatically converted and uploaded using this Hugging Face Space.
Usage with Transformers.js
See the pipeline documentation for image-classification: https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ImageClassificationPipeline
trained-gender
This model is a fine-tuned version of microsoft/resnet-50 on the fair_face dataset. It achieves the following results on the evaluation set:
- Loss: 0.2437
- Accuracy: 0.8986
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4277 | 0.18 | 1000 | 0.4054 | 0.8089 |
| 0.315 | 0.37 | 2000 | 0.3487 | 0.8318 |
| 0.3082 | 0.55 | 3000 | 0.3052 | 0.8633 |
| 0.3235 | 0.74 | 4000 | 0.2899 | 0.8684 |
| 0.2505 | 0.92 | 5000 | 0.2693 | 0.8785 |
| 0.2484 | 1.11 | 6000 | 0.2547 | 0.8889 |
| 0.1933 | 1.29 | 7000 | 0.2521 | 0.8901 |
| 0.1497 | 1.48 | 8000 | 0.2443 | 0.8929 |
| 0.326 | 1.66 | 9000 | 0.2406 | 0.8958 |
| 0.215 | 1.84 | 10000 | 0.2381 | 0.9007 |
| 0.2035 | 2.03 | 11000 | 0.2437 | 0.8986 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
Model info
Created: 2025-11-11
Updated: 2025-11-11
View on Hugging Face