arnabdhar/xlm-roberta-base-wikineural
By arnabdhar · ↓ 5 · ♥ 0 · Updated 2023-12-13
What's in this repo
This page lists the files in arnabdhar/xlm-roberta-base-wikineural, including model.onnx, model_quantized.onnx.
- 2 ONNX models (.onnx files)
- 13 files, including 5 .json, 2 .onnx, 1 .md, 1 .safetensors, 1 .3, 1 .4
- Last updated 2023-12-13
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
xlm-roberta-base-wikineural
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0467
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 37912547
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 100000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0858 | 0.14 | 10000 | 0.0817 |
| 0.0719 | 0.28 | 20000 | 0.0660 |
| 0.0656 | 0.43 | 30000 | 0.0631 |
| 0.0598 | 0.57 | 40000 | 0.0574 |
| 0.0551 | 0.71 | 50000 | 0.0534 |
| 0.0523 | 0.85 | 60000 | 0.0512 |
| 0.0519 | 0.99 | 70000 | 0.0484 |
| 0.0418 | 1.13 | 80000 | 0.0480 |
| 0.042 | 1.28 | 90000 | 0.0469 |
| 0.041 | 1.42 | 100000 | 0.0467 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
Model info
Created: 2023-12-09
Updated: 2023-12-13
View on Hugging Face