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t5-base-lora-finetune-tweetsumm
samuellimabraz/t5-base-lora-finetune-tweetsumm
t5-base-lora-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
- ca8816b8
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-LoRA-TweetSumm-1724689228
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: 1.7954
- Rouge1: 0.4651
- Rouge2: 0.218
- Rougel: 0.3904
- Rougelsum: 0.4291
- Gen Len: 41.8818
- F1: 0.8924
- Precision: 0.8906
- Recall: 0.8943
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: 0.0001
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.3566 | 1.0 | 440 | 1.8523 | 0.4801 | 0.2302 | 0.4078 | 0.4472 | 41.6727 | 0.8942 | 0.8938 | 0.8947 |
| 1.2968 | 2.0 | 880 | 1.7823 | 0.447 | 0.2102 | 0.3795 | 0.4136 | 41.9091 | 0.8929 | 0.8925 | 0.8935 |
| 1.7438 | 3.0 | 1320 | 1.7954 | 0.4651 | 0.218 | 0.3904 | 0.4291 | 41.8818 | 0.8924 | 0.8906 | 0.8943 |
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