opus_mt_zh_en_AIchallenger
This model is a fine-tuned version of opus-mt-zh-en on an AIChallenger2017 dataset. It achieves the following results on the evaluation set:
- Loss: 1.4557
- Bleu: 27.0414
- Meteor: 0.5451
- Gen Len: 15.2255
Model description
More information needed
Intended uses & limitations
This model is used to run the translation model on the client side.
Training and evaluation data
Dataset Source: https://tianchi.aliyun.com/dataset/174937
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 2024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Gen Len |
|---|---|---|---|---|---|---|
| 1.6733 | 1.0 | 156250 | 1.5656 | 25.9104 | 0.5364 | 15.4366 |
| 1.6415 | 2.0 | 312500 | 1.5193 | 26.7033 | 0.5449 | 15.6291 |
| 1.5831 | 3.0 | 468750 | 1.4901 | 27.2345 | 0.5479 | 15.5704 |
| 1.5352 | 4.0 | 625000 | 1.4695 | 27.7312 | 0.5521 | 15.528 |
| 1.4946 | 5.0 | 781250 | 1.4557 | 27.9356 | 0.5543 | 15.548 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
- Downloads last month
- 15
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for rickltt/opus_mt_zh_en_AIchallenger
Base model
Helsinki-NLP/opus-mt-zh-en