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LED-Finetuned-sum-full-note-v2
NazzX1/LED-Finetuned-sum-full-note-v2
LED-Finetuned-sum-full-note-v2 is a machine learning model from NazzX1. 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 transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- led
- Access
- Public
- Created
- Apr 17, 2025
- Updated
- Apr 17, 2025
- SHA
- b745a82f
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. -->
pegasus-Finetuned-sum-full-note-v1
This model is a fine-tuned version of MingZhong/DialogLED-base-16384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8477
- Rouge1: 0.4196
- Rouge2: 0.2672
- Rougel: 0.3179
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| 0.998 | 1.0 | 800 | 0.8796 | 0.4186 | 0.2660 | 0.3165 |
| 0.8535 | 2.0 | 1600 | 0.8477 | 0.4196 | 0.2672 | 0.3179 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
- Library
- transformers
- Type
- led
- Created
- Apr 17, 2025
- Updated
- Apr 17, 2025