metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- indosum
metrics:
- rouge
model-index:
- name: T5-Summarize_Model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: indosum
type: indosum
config: indosum_fold0_source
split: test
args: indosum_fold0_source
metrics:
- name: Rouge1
type: rouge
value: 0.2015
T5-Summarize_Model
This model is a fine-tuned version of t5-small on the indosum dataset. It achieves the following results on the evaluation set:
- Loss: 0.8019
- Rouge1: 0.2015
- Rouge2: 0.1581
- Rougel: 0.201
- Rougelsum: 0.2004
- Gen Len: 19.0
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: 5e-05
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 19 | 0.8400 | 0.1928 | 0.1464 | 0.19 | 0.1902 | 19.0 |
| No log | 2.0 | 38 | 0.8062 | 0.201 | 0.1544 | 0.199 | 0.1986 | 19.0 |
| No log | 3.0 | 57 | 0.8019 | 0.2015 | 0.1581 | 0.201 | 0.2004 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0