metadata
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-lora-0
results: []
summarization-lora-0
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: 0.5656
- Rouge1: 0.4188
- Rouge2: 0.0
- Rougel: 0.4161
- Rougelsum: 0.4157
- 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 |
---|---|---|---|---|---|---|---|---|
1.2271 | 1.0 | 1783 | 0.6275 | 0.491 | 0.0 | 0.4864 | 0.4859 | 1.0 |
0.7893 | 2.0 | 3566 | 0.5955 | 0.4382 | 0.0 | 0.4358 | 0.4345 | 1.0 |
0.7347 | 3.0 | 5349 | 0.5738 | 0.4461 | 0.0 | 0.4432 | 0.4417 | 1.0 |
0.7084 | 4.0 | 7132 | 0.5618 | 0.4416 | 0.0 | 0.4409 | 0.4389 | 1.0 |
0.6976 | 5.0 | 8915 | 0.5656 | 0.4188 | 0.0 | 0.4161 | 0.4157 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1