Downloads · 30 days
6
24% of all-time downloads
t5-base-lora-finetune-tweetsumm-1759927674
Dikshant182004/t5-base-lora-finetune-tweetsumm-1759927674
t5-base-lora-finetune-tweetsumm-1759927674 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. --
All-time downloads
25
Public
Repo size
7.9 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors7.1 MB · 68%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Oct 8, 2025
- Updated
- Oct 8, 2025
- SHA
- 93602d8d
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-1759927674
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: 1.7857
- Rouge1: 0.4418
- Rouge2: 0.2109
- Rougel: 0.3724
- Rougelsum: 0.4058
- Gen Len: 48.6818
- F1: 0.8889
- Precision: 0.8855
- Recall: 0.8926
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.1175 | 1.0 | 110 | 1.8794 | 0.4174 | 0.191 | 0.3533 | 0.3875 | 49.9818 | 0.884 | 0.8807 | 0.8876 |
| 1.8042 | 2.0 | 220 | 1.8062 | 0.4207 | 0.1954 | 0.3554 | 0.3864 | 49.0727 | 0.8868 | 0.8832 | 0.8906 |
| 1.5646 | 3.0 | 330 | 1.7857 | 0.4418 | 0.2109 | 0.3724 | 0.4058 | 48.6818 | 0.8889 | 0.8855 | 0.8926 |
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