File size: 1,388 Bytes
fbf03e2 ed716e3 fbf03e2 ed716e3 fbf03e2 ed716e3 fbf03e2 ed716e3 fbf03e2 ed716e3 fbf03e2 ed716e3 fbf03e2 ed716e3 fbf03e2 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 |
---
library_name: transformers
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
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: 0.2302
- Bleu Score: 73.8994
- Gen Len: 13.2
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:-------:|
| 0.4035 | 1.0 | 1047 | 0.2302 | 73.8994 | 13.2 |
### Framework versions
- Transformers 4.45.0
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.20.0
|