metadata
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
datasets:
- thaisum
metrics:
- rouge
model-index:
- name: mt5_thaisum_finetune
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: thaisum
type: thaisum
config: thaisum
split: validation
args: thaisum
metrics:
- name: Rouge1
type: rouge
value: 0.2022
mt5_thaisum_finetune
This model is a fine-tuned version of google/mt5-base on the thaisum dataset. It achieves the following results on the evaluation set:
- Loss: 0.3039
- Rouge1: 0.2022
- Rouge2: 0.0808
- Rougel: 0.2023
- Rougelsum: 0.2019
- Gen Len: 18.9995
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.0742 | 1.0 | 5000 | 0.3272 | 0.1713 | 0.0551 | 0.1716 | 0.1714 | 18.9945 |
| 1.7874 | 2.0 | 10000 | 0.3073 | 0.1943 | 0.0747 | 0.195 | 0.1941 | 18.997 |
| 1.6341 | 3.0 | 15000 | 0.3035 | 0.2006 | 0.0807 | 0.2007 | 0.2002 | 19.0 |
| 1.4501 | 4.0 | 20000 | 0.3039 | 0.2022 | 0.0808 | 0.2023 | 0.2019 | 18.9995 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3