nananatsu/opus-mt-en-zh-finetuned-audio-product
By nananatsu · ↓ 2 · ♥ 0 · Updated 2025-02-14
What's in this repo
This page lists the files in nananatsu/opus-mt-en-zh-finetuned-audio-product, including decoder_model_merged.onnx, decoder_model_merged_quantized.onnx, encoder_model.onnx and more.
- 4 ONNX models (.onnx files)
- 23 files, including 11 .json, 4 .onnx, 4 .spm, 1 .md, 1 .safetensors, 1 .bin
- Last updated 2025-02-14
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/decoder_model_merged.onnx | — | Download |
| onnx/decoder_model_merged_quantized.onnx | — | Download |
| onnx/encoder_model.onnx | — | Download |
| onnx/encoder_model_quantized.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
opus-mt-en-zh-finetuned-audio-product
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-zh on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0662
- Bleu: 60.5401
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 3.7442 | 1.0 | 66 | 0.1319 | 37.4394 |
| 0.1694 | 2.0 | 132 | 0.0904 | 48.8190 |
| 0.1179 | 3.0 | 198 | 0.0773 | 51.3552 |
| 0.0662 | 4.0 | 264 | 0.0716 | 51.7823 |
| 0.0542 | 5.0 | 330 | 0.0681 | 54.9762 |
| 0.0445 | 6.0 | 396 | 0.0668 | 55.1506 |
| 0.0308 | 7.0 | 462 | 0.0655 | 56.1614 |
| 0.0274 | 8.0 | 528 | 0.0656 | 57.7665 |
| 0.0246 | 9.0 | 594 | 0.0656 | 58.8837 |
| 0.019 | 10.0 | 660 | 0.0654 | 59.1559 |
| 0.017 | 11.0 | 726 | 0.0661 | 60.0839 |
| 0.0151 | 12.0 | 792 | 0.0658 | 58.4574 |
| 0.013 | 13.0 | 858 | 0.0660 | 59.3195 |
| 0.0119 | 14.0 | 924 | 0.0657 | 59.5030 |
| 0.0118 | 15.0 | 990 | 0.0662 | 60.0147 |
| 0.0104 | 16.0 | 1056 | 0.0661 | 60.6406 |
| 0.0101 | 17.0 | 1122 | 0.0662 | 60.3492 |
| 0.01 | 18.0 | 1188 | 0.0662 | 60.7125 |
| 0.0097 | 19.0 | 1254 | 0.0662 | 60.4941 |
| 0.0096 | 20.0 | 1320 | 0.0662 | 60.5401 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
Model info
Created: 2025-01-11
Updated: 2025-02-14
View on Hugging FaceFiles (23)
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