File size: 2,150 Bytes
65dc3d3 1168cef 65dc3d3 613174b 65dc3d3 613174b 65dc3d3 b2ed9cb 65dc3d3 613174b b2ed9cb 65dc3d3 c91ccb9 65dc3d3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
---
tags:
- generated_from_trainer
metrics:
- bleu
base_model: fnlp/bart-base-chinese
model-index:
- name: cantonese-chinese-translation
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# cantonese-chinese-translation
This model is a fine-tuned version of [fnlp/bart-base-chinese](https://huggingface.co/fnlp/bart-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2258
- Bleu: 62.1085
- Chrf: 60.1854
- Gen Len: 12.8755
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|
| 0.3606 | 0.48 | 1000 | 0.2592 | 60.9844 | 58.8851 | 12.8446 |
| 0.3059 | 0.96 | 2000 | 0.2291 | 61.9606 | 60.1201 | 12.8621 |
| 0.2296 | 1.44 | 3000 | 0.2254 | 61.9458 | 60.0434 | 12.8578 |
| 0.2231 | 1.92 | 4000 | 0.2176 | 61.9617 | 59.9299 | 12.8827 |
| 0.174 | 2.39 | 5000 | 0.2290 | 61.9661 | 59.8844 | 12.9068 |
| 0.171 | 2.87 | 6000 | 0.2258 | 62.1085 | 60.1854 | 12.8755 |
| 0.1346 | 3.35 | 7000 | 0.2334 | 61.4554 | 59.5055 | 12.8175 |
| 0.1285 | 3.83 | 8000 | 0.2408 | 61.3332 | 59.3276 | 12.8412 |
| 0.1061 | 4.31 | 9000 | 0.2530 | 61.6505 | 59.614 | 12.8566 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.13.3
|