metadata
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-3
results: []
summarization-lora-3
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: 0.6087
- Rouge1: 0.4049
- Rouge2: 0.0
- Rougel: 0.4028
- Rougelsum: 0.4042
- 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: 5e-05
- train_batch_size: 8
- 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 |
---|---|---|---|---|---|---|---|---|
1.3948 | 1.0 | 1784 | 0.6978 | 0.3931 | 0.0 | 0.3957 | 0.3954 | 1.0 |
0.8544 | 2.0 | 3568 | 0.6352 | 0.4133 | 0.0 | 0.4123 | 0.4139 | 1.0 |
0.791 | 3.0 | 5352 | 0.6227 | 0.4051 | 0.0 | 0.4033 | 0.4045 | 1.0 |
0.7631 | 4.0 | 7136 | 0.6149 | 0.3884 | 0.0 | 0.3851 | 0.3881 | 1.0 |
0.7508 | 5.0 | 8920 | 0.6087 | 0.4049 | 0.0 | 0.4028 | 0.4042 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1