File size: 1,988 Bytes
f1068ff 9f78c1c f1068ff |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization-base-1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# summarization-base-1
This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5103
- Rouge1: 0.4427
- Rouge2: 0.0
- Rougel: 0.4423
- Rougelsum: 0.4403
- 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: 4
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.6316 | 1.0 | 3566 | 0.4807 | 0.4602 | 0.0 | 0.4604 | 0.4565 | 1.0 |
| 0.4336 | 2.0 | 7132 | 0.4717 | 0.4661 | 0.0 | 0.466 | 0.4622 | 1.0 |
| 0.3363 | 3.0 | 10698 | 0.4723 | 0.4799 | 0.0 | 0.479 | 0.4762 | 1.0 |
| 0.2656 | 4.0 | 14264 | 0.4825 | 0.4713 | 0.0 | 0.4703 | 0.4666 | 1.0 |
| 0.219 | 5.0 | 17830 | 0.5103 | 0.4427 | 0.0 | 0.4423 | 0.4403 | 1.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|