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flan-t5-base
nikitha2006/flan-t5-base
flan-t5-base is a machine learning model from nikitha2006. 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
- Feb 15, 2025
- Updated
- Feb 15, 2025
- SHA
- c5d7d5be
Base models
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. -->
flan-t5-base
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5939
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 7 | 3.4902 |
| 3.8973 | 2.0 | 14 | 2.1025 |
| 2.9243 | 3.0 | 21 | 1.7897 |
| 2.9243 | 4.0 | 28 | 1.3125 |
| 2.2081 | 5.0 | 35 | 0.9526 |
| 1.6758 | 6.0 | 42 | 0.8451 |
| 1.6758 | 7.0 | 49 | 0.6966 |
| 1.405 | 8.0 | 56 | 0.6964 |
| 1.1894 | 9.0 | 63 | 0.6179 |
| 1.0695 | 10.0 | 70 | 0.5889 |
| 1.0695 | 11.0 | 77 | 0.6051 |
| 1.0252 | 12.0 | 84 | 0.5939 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0
- Library
- peft
- License
- apache-2.0
- Created
- Feb 15, 2025
- Updated
- Feb 15, 2025