metadata
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-1
results: []
summarization-lora-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: 0.5838
- Rouge1: 0.5174
- Rouge2: 0.0
- Rougel: 0.523
- Rougelsum: 0.5165
- 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 |
|---|---|---|---|---|---|---|---|---|
| 1.3911 | 1.0 | 1783 | 0.6611 | 0.4074 | 0.0 | 0.4062 | 0.4066 | 1.0 |
| 0.8526 | 2.0 | 3566 | 0.6167 | 0.5108 | 0.0 | 0.515 | 0.51 | 1.0 |
| 0.7928 | 3.0 | 5349 | 0.5968 | 0.4966 | 0.0 | 0.5042 | 0.4969 | 1.0 |
| 0.7651 | 4.0 | 7132 | 0.5860 | 0.5171 | 0.0 | 0.5228 | 0.5173 | 1.0 |
| 0.7528 | 5.0 | 8915 | 0.5838 | 0.5174 | 0.0 | 0.523 | 0.5165 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1