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t5-base-lora-finetune-tweetsumm-1759926273
Dikshant182004/t5-base-lora-finetune-tweetsumm-1759926273
t5-base-lora-finetune-tweetsumm-1759926273 is a machine learning model from Dikshant182004. 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
- Oct 8, 2025
- Updated
- Oct 8, 2025
- SHA
- 83894185
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-finetune-tweetsumm-1759926273
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: 1.8100
- Rouge1: 0.4551
- Rouge2: 0.2106
- Rougel: 0.3742
- Rougelsum: 0.4167
- Gen Len: 47.5636
- F1: 0.8917
- Precision: 0.8879
- Recall: 0.8958
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.0742 | 1.0 | 110 | 1.8740 | 0.4377 | 0.2001 | 0.361 | 0.4021 | 49.3273 | 0.8863 | 0.8819 | 0.8909 |
| 1.8448 | 2.0 | 220 | 1.8243 | 0.4569 | 0.2143 | 0.3752 | 0.4211 | 47.3818 | 0.8916 | 0.8886 | 0.8949 |
| 1.5995 | 3.0 | 330 | 1.8100 | 0.4551 | 0.2106 | 0.3742 | 0.4167 | 47.5636 | 0.8917 | 0.8879 | 0.8958 |
Framework versions
- PEFT 0.17.1
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Library
- peft
- License
- apache-2.0
- Created
- Oct 8, 2025
- Updated
- Oct 8, 2025