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t5-small-lora-finetune-tweetsumm
samuellimabraz/t5-small-lora-finetune-tweetsumm
t5-small-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
- f9d2f344
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-LoRA-TweetSumm-1724701402
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: 2.0811
- Rouge1: 0.4387
- Rouge2: 0.196
- Rougel: 0.3605
- Rougelsum: 0.4055
- Gen Len: 49.5909
- F1: 0.8896
- Precision: 0.8881
- Recall: 0.8913
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: 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.3972 | 1.0 | 110 | 2.1384 | 0.4219 | 0.1801 | 0.3545 | 0.3925 | 49.9818 | 0.8833 | 0.8806 | 0.8861 |
| 2.2593 | 2.0 | 220 | 2.0982 | 0.4125 | 0.1843 | 0.3448 | 0.3837 | 49.9091 | 0.8853 | 0.8822 | 0.8886 |
| 1.9318 | 3.0 | 330 | 2.0811 | 0.4387 | 0.196 | 0.3605 | 0.4055 | 49.5909 | 0.8896 | 0.8881 | 0.8913 |
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