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finetuning_summarization
arzans9/finetuning_summarization
finetuning_summarization is a machine learning model from arzans9. 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
- encoder-decoder
- Access
- Public
- Created
- May 29, 2024
- Updated
- May 29, 2024
- SHA
- 206ece67
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. -->
finetuning_summarization
This model is a fine-tuned version of cahya/bert2bert-indonesian-summarization on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6759
- Rouge1: 0.8455
- Rouge2: 0.742
- Rougel: 0.8486
- Rougelsum: 0.8475
- Gen Len: 23.7368
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 5 | 1.3699 | 0.8443 | 0.7258 | 0.8426 | 0.8435 | 25.8421 |
| No log | 2.0 | 10 | 1.0257 | 0.8282 | 0.7115 | 0.8293 | 0.8275 | 25.0 |
| No log | 3.0 | 15 | 0.7871 | 0.8384 | 0.7277 | 0.8397 | 0.8396 | 24.3158 |
| No log | 4.0 | 20 | 0.7078 | 0.8339 | 0.7318 | 0.8358 | 0.8348 | 23.4211 |
| No log | 5.0 | 25 | 0.6994 | 0.843 | 0.7396 | 0.8451 | 0.845 | 24.0 |
| No log | 6.0 | 30 | 0.6832 | 0.8445 | 0.7413 | 0.8419 | 0.842 | 23.4737 |
| No log | 7.0 | 35 | 0.6768 | 0.8429 | 0.742 | 0.8451 | 0.8448 | 23.6842 |
| No log | 8.0 | 40 | 0.6736 | 0.843 | 0.7396 | 0.8451 | 0.845 | 23.6842 |
| No log | 9.0 | 45 | 0.6750 | 0.843 | 0.7396 | 0.8451 | 0.845 | 23.6842 |
| No log | 10.0 | 50 | 0.6759 | 0.8455 | 0.742 | 0.8486 | 0.8475 | 23.7368 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- encoder-decoder
- License
- apache-2.0
- Created
- May 29, 2024
- Updated
- May 29, 2024