metadata
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-base-1
results: []
summarization-base-1
This model is a fine-tuned version of LazarusNLP/IndoNanoT5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7342
- Rouge1: 0.4659
- Rouge2: 0.0
- Rougel: 0.4632
- Rougelsum: 0.4636
- Gen Len: 1.0
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: 0.001
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.1936 | 1.0 | 892 | 0.7944 | 0.7769 | 0.0 | 0.7776 | 0.7776 | 1.0 |
0.678 | 2.0 | 1784 | 0.6952 | 0.7516 | 0.0 | 0.7464 | 0.7488 | 1.0 |
0.4823 | 3.0 | 2676 | 0.6426 | 0.752 | 0.0 | 0.7509 | 0.7499 | 1.0 |
0.3348 | 4.0 | 3568 | 0.6651 | 0.7449 | 0.0 | 0.7455 | 0.7449 | 1.0 |
0.1967 | 5.0 | 4460 | 0.7342 | 0.7526 | 0.0 | 0.7508 | 0.7516 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1