usvsnsp/code-vs-nl
By usvsnsp · ↓ 15 · ♥ 2 · Updated 2024-02-23
What's in this repo
This page lists the files in usvsnsp/code-vs-nl, including model.onnx.
- 1 ONNX models (.onnx files)
- 20 files, including 8 .json, 3 .ip-26-0-128-22, 2 .txt, 2 .bin, 1 .md, 1 .safetensors
- Last updated 2024-02-23
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/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
code-vs-nl
This model is a fine-tuned version of distilbert-base-uncased on bookcorpus for text and codeparrot/github-code for code datasets. It achieves the following results on the evaluation set:
- Loss: 0.5180
- Accuracy: 0.9951
- F1 Score: 0.9950
Model description
As it's a finetuned model, it's architecture is same as distilbert-base-uncased for Sequence Classification
Intended uses & limitations
Can be used to classify documents into text and code
Training and evaluation data
It is a mix of above two datasets, equally random sampled
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-07
- train_batch_size: 256
- eval_batch_size: 1024
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| 0.5732 | 0.07 | 500 | 0.5658 | 0.9934 | 0.9934 |
| 0.5254 | 0.14 | 1000 | 0.5180 | 0.9951 | 0.9950 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
Model info
Created: 2023-01-25
Updated: 2024-02-23
View on Hugging FaceFiles (20)
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