File size: 2,321 Bytes
ff3b2d3 f9369be ff3b2d3 f9369be ff3b2d3 f9369be ff3b2d3 8ad71e1 f9369be ff3b2d3 8ad71e1 ff3b2d3 |
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 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
datasets:
- id_liputan6
metrics:
- rouge
model-index:
- name: liputan6-seq_bn-rf16
results:
- task:
name: Summarization
type: summarization
dataset:
name: id_liputan6 canonical
type: id_liputan6
config: canonical
split: validation
args: canonical
metrics:
- name: Rouge1
type: rouge
value: 44.408
---
<!-- 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. -->
# liputan6-seq_bn-rf16
This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2554
- Rouge1: 44.408
- Rouge2: 35.788
- Rougel: 40.8449
- Rougelsum: 43.0054
- Gen Len: 62.247
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.9013 | 1.0 | 63 | 0.3600 | 40.5674 | 32.5892 | 37.7471 | 39.1368 | 46.887 |
| 0.4754 | 2.0 | 126 | 0.2958 | 43.3031 | 34.5149 | 39.7514 | 41.863 | 56.767 |
| 0.3811 | 3.0 | 189 | 0.2629 | 43.4511 | 34.6775 | 39.9831 | 42.0606 | 57.898 |
| 0.3317 | 4.0 | 252 | 0.2610 | 43.9259 | 35.2198 | 40.3143 | 42.5364 | 57.815 |
| 0.299 | 5.0 | 315 | 0.2554 | 44.3826 | 35.7034 | 40.7597 | 42.9985 | 58.818 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|