Commit ·
7159f6e
1
Parent(s): c3dc724
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-V5
|
| 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-V5
|
| 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: 0.3694
|
| 20 |
+
- Bleu: 77.0736
|
| 21 |
+
- Gen Len: 10.0475
|
| 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 |
+
| 1.195 | 0.01 | 500 | 0.9492 | 43.0845 | 7.2405 |
|
| 55 |
+
| 0.978 | 0.01 | 1000 | 0.7804 | 61.0671 | 9.7255 |
|
| 56 |
+
| 0.8418 | 0.02 | 1500 | 0.6798 | 64.3811 | 9.9025 |
|
| 57 |
+
| 0.8148 | 0.03 | 2000 | 0.6046 | 66.1944 | 10.043 |
|
| 58 |
+
| 0.7622 | 0.04 | 2500 | 0.5513 | 68.2851 | 10.1215 |
|
| 59 |
+
| 0.7199 | 0.04 | 3000 | 0.5146 | 69.7161 | 10.0795 |
|
| 60 |
+
| 0.7898 | 0.05 | 3500 | 0.4869 | 71.1868 | 10.079 |
|
| 61 |
+
| 0.6921 | 0.06 | 4000 | 0.4648 | 72.4203 | 10.0345 |
|
| 62 |
+
| 0.6827 | 0.07 | 4500 | 0.4490 | 73.2133 | 10.039 |
|
| 63 |
+
| 0.6102 | 0.07 | 5000 | 0.4355 | 73.6841 | 10.078 |
|
| 64 |
+
| 0.5805 | 0.08 | 5500 | 0.4176 | 74.2559 | 10.059 |
|
| 65 |
+
| 0.6806 | 0.09 | 6000 | 0.4081 | 74.7389 | 10.0655 |
|
| 66 |
+
| 0.6544 | 0.09 | 6500 | 0.3958 | 75.2603 | 10.025 |
|
| 67 |
+
| 0.6244 | 0.1 | 7000 | 0.3904 | 75.9306 | 10.0565 |
|
| 68 |
+
| 0.7212 | 0.11 | 7500 | 0.3822 | 76.3268 | 10.0505 |
|
| 69 |
+
| 0.5446 | 0.12 | 8000 | 0.3785 | 76.5306 | 10.0505 |
|
| 70 |
+
| 0.5574 | 0.12 | 8500 | 0.3741 | 76.7101 | 10.0545 |
|
| 71 |
+
| 0.6265 | 0.13 | 9000 | 0.3721 | 76.8858 | 10.043 |
|
| 72 |
+
| 0.5379 | 0.14 | 9500 | 0.3695 | 77.001 | 10.051 |
|
| 73 |
+
| 0.6164 | 0.14 | 10000 | 0.3694 | 77.0736 | 10.0475 |
|
| 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
|