File size: 3,320 Bytes
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 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: cantonese-chinese-parallel-corpus-bart-compare-alpha
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-parallel-corpus-bart-compare-alpha
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: 1.2307
- Bleu: 28.1911
- Chrf: 27.3934
- Gen Len: 13.1593
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|
| 1.8245 | 0.14 | 1000 | 1.5392 | 23.4094 | 22.9586 | 12.9471 |
| 1.6283 | 0.29 | 2000 | 1.4433 | 24.6312 | 24.1038 | 12.9882 |
| 1.5527 | 0.43 | 3000 | 1.4074 | 25.4368 | 24.7944 | 13.0385 |
| 1.5125 | 0.58 | 4000 | 1.3743 | 25.6532 | 25.1073 | 13.0069 |
| 1.4572 | 0.72 | 5000 | 1.3468 | 26.2054 | 25.6527 | 13.0221 |
| 1.451 | 0.87 | 6000 | 1.3249 | 26.3433 | 25.7717 | 13.0345 |
| 1.4087 | 1.01 | 7000 | 1.3162 | 26.7569 | 26.0931 | 13.1037 |
| 1.296 | 1.16 | 8000 | 1.2961 | 26.7816 | 26.1834 | 13.0488 |
| 1.285 | 1.3 | 9000 | 1.2881 | 27.1895 | 26.4474 | 13.1257 |
| 1.281 | 1.45 | 10000 | 1.2778 | 27.248 | 26.5723 | 13.072 |
| 1.2809 | 1.59 | 11000 | 1.2772 | 27.3645 | 26.7016 | 13.0937 |
| 1.2741 | 1.74 | 12000 | 1.2568 | 27.3857 | 26.7455 | 13.0646 |
| 1.2658 | 1.88 | 13000 | 1.2552 | 27.4927 | 26.8279 | 13.0988 |
| 1.2412 | 2.03 | 14000 | 1.2632 | 27.5154 | 26.9238 | 13.0482 |
| 1.1303 | 2.17 | 15000 | 1.2627 | 27.7288 | 27.0753 | 13.0828 |
| 1.1449 | 2.32 | 16000 | 1.2596 | 27.7628 | 27.1038 | 13.0667 |
| 1.1352 | 2.46 | 17000 | 1.2465 | 27.9487 | 27.1672 | 13.1585 |
| 1.151 | 2.61 | 18000 | 1.2426 | 27.9699 | 27.2496 | 13.1294 |
| 1.1361 | 2.75 | 19000 | 1.2348 | 27.9343 | 27.218 | 13.0994 |
| 1.1368 | 2.9 | 20000 | 1.2307 | 28.1911 | 27.3934 | 13.1593 |
| 1.1012 | 3.04 | 21000 | 1.2487 | 28.1384 | 27.4055 | 13.1253 |
| 1.0201 | 3.19 | 22000 | 1.2482 | 28.0577 | 27.3169 | 13.1299 |
| 1.0274 | 3.33 | 23000 | 1.2479 | 28.149 | 27.4087 | 13.1401 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
|