Commit ·
74f1a7d
1
Parent(s): d70cf5c
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- bleu
|
| 7 |
+
model-index:
|
| 8 |
+
- name: Vigec-V3
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# Vigec-V3
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 0.2522
|
| 20 |
+
- Bleu: 84.4788
|
| 21 |
+
- Gen Len: 9.847
|
| 22 |
+
|
| 23 |
+
## Model description
|
| 24 |
+
|
| 25 |
+
More information needed
|
| 26 |
+
|
| 27 |
+
## Intended uses & limitations
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Training and evaluation data
|
| 32 |
+
|
| 33 |
+
More information needed
|
| 34 |
+
|
| 35 |
+
## Training procedure
|
| 36 |
+
|
| 37 |
+
### Training hyperparameters
|
| 38 |
+
|
| 39 |
+
The following hyperparameters were used during training:
|
| 40 |
+
- learning_rate: 1e-05
|
| 41 |
+
- train_batch_size: 16
|
| 42 |
+
- eval_batch_size: 8
|
| 43 |
+
- seed: 42
|
| 44 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 45 |
+
- lr_scheduler_type: linear
|
| 46 |
+
- lr_scheduler_warmup_steps: 500
|
| 47 |
+
- training_steps: 10000
|
| 48 |
+
- mixed_precision_training: Native AMP
|
| 49 |
+
|
| 50 |
+
### Training results
|
| 51 |
+
|
| 52 |
+
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|
| 53 |
+
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
|
| 54 |
+
| 0.8764 | 0.0 | 500 | 0.6120 | 68.0114 | 8.4626 |
|
| 55 |
+
| 0.6538 | 0.0 | 1000 | 0.4780 | 76.7403 | 10.015 |
|
| 56 |
+
| 0.6234 | 0.01 | 1500 | 0.4207 | 78.1726 | 9.8394 |
|
| 57 |
+
| 0.4513 | 0.01 | 2000 | 0.3845 | 79.1939 | 9.8914 |
|
| 58 |
+
| 0.4153 | 0.01 | 2500 | 0.3580 | 80.171 | 9.7298 |
|
| 59 |
+
| 0.5129 | 0.01 | 3000 | 0.3381 | 80.8668 | 9.8636 |
|
| 60 |
+
| 0.5073 | 0.01 | 3500 | 0.3246 | 81.5543 | 9.81 |
|
| 61 |
+
| 0.4623 | 0.01 | 4000 | 0.3106 | 82.1255 | 9.8684 |
|
| 62 |
+
| 0.4444 | 0.02 | 4500 | 0.2973 | 82.5565 | 9.848 |
|
| 63 |
+
| 0.4322 | 0.02 | 5000 | 0.2892 | 82.9623 | 9.872 |
|
| 64 |
+
| 0.5029 | 0.02 | 5500 | 0.2803 | 83.3084 | 9.8648 |
|
| 65 |
+
| 0.3686 | 0.02 | 6000 | 0.2765 | 83.4828 | 9.8602 |
|
| 66 |
+
| 0.4123 | 0.02 | 6500 | 0.2693 | 83.7491 | 9.8432 |
|
| 67 |
+
| 0.3593 | 0.03 | 7000 | 0.2674 | 83.8149 | 9.811 |
|
| 68 |
+
| 0.3684 | 0.03 | 7500 | 0.2630 | 84.1745 | 9.8668 |
|
| 69 |
+
| 0.3683 | 0.03 | 8000 | 0.2590 | 84.2294 | 9.8412 |
|
| 70 |
+
| 0.3581 | 0.03 | 8500 | 0.2568 | 84.3428 | 9.8582 |
|
| 71 |
+
| 0.3769 | 0.03 | 9000 | 0.2527 | 84.4367 | 9.8598 |
|
| 72 |
+
| 0.4479 | 0.03 | 9500 | 0.2522 | 84.4749 | 9.847 |
|
| 73 |
+
| 0.2856 | 0.04 | 10000 | 0.2522 | 84.4788 | 9.847 |
|
| 74 |
+
|
| 75 |
+
|
| 76 |
+
### Framework versions
|
| 77 |
+
|
| 78 |
+
- Transformers 4.26.0
|
| 79 |
+
- Pytorch 1.13.1+cu116
|
| 80 |
+
- Datasets 2.9.0
|
| 81 |
+
- Tokenizers 0.13.2
|