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t5-small-qlora-finetune-tweetsumm
samuellimabraz/t5-small-qlora-finetune-tweetsumm
t5-small-qlora-finetune-tweetsumm is a machine learning model from samuellimabraz. 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 peft. 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
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Aug 26, 2024
- Updated
- Aug 26, 2024
- SHA
- d7f4ba3b
Base models
Datasets
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. -->
t5-small-QLoRA-TweetSumm-1724713795
This model is a fine-tuned version of google-t5/t5-small on the Andyrasika/TweetSumm-tuned dataset. It achieves the following results on the evaluation set:
- Loss: 2.0940
- Rouge1: 0.4298
- Rouge2: 0.1915
- Rougel: 0.3559
- Rougelsum: 0.3956
- Gen Len: 47.8091
- F1: 0.887
- Precision: 0.8838
- Recall: 0.8904
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.3641 | 1.0 | 110 | 2.2019 | 0.4172 | 0.1774 | 0.3518 | 0.386 | 47.7636 | 0.8828 | 0.8806 | 0.8852 |
| 2.2228 | 2.0 | 220 | 2.1040 | 0.419 | 0.1789 | 0.3477 | 0.3827 | 48.1182 | 0.8846 | 0.882 | 0.8875 |
| 2.0174 | 3.0 | 330 | 2.0940 | 0.4298 | 0.1915 | 0.3559 | 0.3956 | 47.8091 | 0.887 | 0.8838 | 0.8904 |
Framework versions
- PEFT 0.12.1.dev0
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Aug 26, 2024
- Updated
- Aug 26, 2024