File size: 2,046 Bytes
466e96a d263f09 466e96a d263f09 466e96a d263f09 466e96a d263f09 466e96a |
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 |
---
tags:
- generated_from_trainer
datasets:
- indosum
metrics:
- rouge
model-index:
- name: t5-base-indonesian-summarization-cased-finetuned-indosum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: indosum
type: indosum
config: indosum_fold0_source
split: validation
args: indosum_fold0_source
metrics:
- name: Rouge1
type: rouge
value: 0.3278
---
<!-- 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. -->
# t5-base-indonesian-summarization-cased-finetuned-indosum
This model is a fine-tuned version of [panggi/t5-base-indonesian-summarization-cased](https://huggingface.co/panggi/t5-base-indonesian-summarization-cased) on the indosum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5884
- Rouge1: 0.3278
- Rouge2: 0.2868
- Rougel: 0.32
- Rougelsum: 0.3198
- Gen Len: 19.0
## 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: 5.6e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.3815 | 1.0 | 4754 | 0.5584 | 0.3281 | 0.2866 | 0.3202 | 0.32 | 19.0 |
| 0.3207 | 2.0 | 9508 | 0.5884 | 0.3278 | 0.2868 | 0.32 | 0.3198 | 19.0 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
|