File size: 1,995 Bytes
8162219 92c7426 8162219 92c7426 8162219 92c7426 8162219 92c7426 8162219 |
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 |
---
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: indosum-base-0
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. -->
# indosum-base-0
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: 0.7170
- Rouge1: 72.5364
- Rouge2: 65.2519
- Rougel: 69.5637
- Rougelsum: 71.6884
- Gen Len: 98.9053
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.2132 | 1.0 | 892 | 0.7742 | 67.4414 | 59.7409 | 64.517 | 66.4918 | 94.092 |
| 0.686 | 2.0 | 1784 | 0.6673 | 70.2138 | 62.8202 | 67.1553 | 69.3063 | 100.2933 |
| 0.491 | 3.0 | 2676 | 0.6274 | 71.2142 | 63.9943 | 68.2722 | 70.2971 | 100.944 |
| 0.343 | 4.0 | 3568 | 0.6469 | 71.7114 | 64.489 | 68.7214 | 70.7949 | 98.8227 |
| 0.2059 | 5.0 | 4460 | 0.7170 | 72.5364 | 65.2519 | 69.5637 | 71.6884 | 98.9053 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|