seanghay/khmer-text-classification-roberta
By seanghay · ↓ 12 · ♥ 0 · Updated 2023-05-14
What's in this repo
This page lists the files in seanghay/khmer-text-classification-roberta, including model.onnx.
- 1 ONNX models (.onnx files)
- 14 files, including 4 .json, 2 .bin, 1 .md, 1 .onnx, 1 .safetensors, 1 .1
- Last updated 2023-05-14
ONNX files
| File | Size | Download |
|---|---|---|
| model.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
khmer-text-classification-roberta
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8290
- Accuracy: 0.6477
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: 44
- eval_batch_size: 44
- 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 |
|---|---|---|---|---|
| 0.983 | 1.0 | 1228 | 0.8927 | 0.6327 |
| 0.8734 | 2.0 | 2456 | 0.8639 | 0.6417 |
| 0.8008 | 3.0 | 3684 | 0.8296 | 0.648 |
| 0.7483 | 4.0 | 4912 | 0.8290 | 0.6477 |
Framework versions
- Transformers 4.29.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
Model info
Created: 2023-05-13
Updated: 2023-05-14
View on Hugging Face