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indosum-base-0
apwic/indosum-base-0
indosum-base-0 is a machine learning model from apwic. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Jul 18, 2024
- Updated
- Jul 19, 2024
- SHA
- e975ff2d
Base models
Model card
From the Hugging Face model README
<!-- 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 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7170
- Rouge1: 72.8591
- Rouge2: 65.7981
- Rougel: 69.8759
- Rougelsum: 72.0557
- Gen Len: 99.276
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
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Languages
- id
- Created
- Jul 18, 2024
- Updated
- Jul 19, 2024