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
- 111
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for rickltt/opus_mt_zh_en_AIchallenger
Base model
Helsinki-NLP/opus-mt-zh-en