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t5-base-qlora-finetune-tweetsumm
samuellimabraz/t5-base-qlora-finetune-tweetsumm
t5-base-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 28, 2024
- Updated
- Aug 28, 2024
- SHA
- f16d96e4
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-base-qlora-finetune-tweetsumm-1724817707
This model is a fine-tuned version of google-t5/t5-base on the Andyrasika/TweetSumm-tuned dataset. It achieves the following results on the evaluation set:
- Loss: 1.7934
- Rouge1: 0.4708
- Rouge2: 0.2246
- Rougel: 0.3984
- Rougelsum: 0.4357
- Gen Len: 49.4091
- F1: 0.8942
- Precision: 0.8941
- Recall: 0.8945
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
- lr_scheduler_warmup_steps: 2
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.062 | 1.0 | 110 | 1.8472 | 0.4633 | 0.2177 | 0.3919 | 0.428 | 49.7273 | 0.8911 | 0.8897 | 0.8927 |
| 1.7853 | 2.0 | 220 | 1.8120 | 0.4633 | 0.2203 | 0.3941 | 0.4285 | 49.4273 | 0.8953 | 0.8945 | 0.8963 |
| 1.5952 | 3.0 | 330 | 1.7934 | 0.4708 | 0.2246 | 0.3984 | 0.4357 | 49.4091 | 0.8942 | 0.8941 | 0.8945 |
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 28, 2024
- Updated
- Aug 28, 2024