File size: 1,891 Bytes
fbf03e2 ed716e3 fbf03e2 ed716e3 fbf03e2 751a32d fbf03e2 ed716e3 fbf03e2 74ac15b fbf03e2 ed716e3 21ebd5a fbf03e2 74ac15b fbf03e2 751a32d 74ac15b fbf03e2 ded0611 ed716e3 ded0611 ed716e3 |
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 |
---
library_name: transformers
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: ViNormT5
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. -->
# ViNormT5
This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2324
- Bleu Score: 79.5557
- Precision: 56.9892
- Recall: 56.9892
- Gen Len: 12.7969
- Err: 56.9892
## 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: 0.0001
- 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall | Gen Len | Err |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
| 0.4672 | 1.0 | 419 | 0.2390 | 76.7871 | 49.7013 | 49.7013 | 12.8292 | 49.7013 |
| 0.1742 | 2.0 | 838 | 0.2173 | 77.9698 | 54.0024 | 54.0024 | 12.8076 | 54.0024 |
| 0.0814 | 3.0 | 1257 | 0.2010 | 79.204 | 56.6308 | 56.6308 | 12.7754 | 56.6308 |
| 0.0382 | 4.0 | 1676 | 0.2324 | 79.5557 | 56.9892 | 56.9892 | 12.7969 | 56.9892 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
|