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pegasus-model
Akhilsplendid/pegasus-model
pegasus-model is a machine learning model from Akhilsplendid. 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
- pegasus
- Access
- Public
- Created
- Aug 24, 2023
- Updated
- Aug 24, 2023
- SHA
- a7af0b8a
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-model
This model is a fine-tuned version of amagzari/pegasus-cnn_dailymail-finetuned-samsum-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1602
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2222 | 0.8 | 10 | 1.6816 |
| 2.2663 | 1.61 | 20 | 1.6594 |
| 2.0153 | 2.41 | 30 | 1.6221 |
| 2.1572 | 3.22 | 40 | 1.5758 |
| 2.0548 | 4.02 | 50 | 1.5208 |
| 1.9995 | 4.82 | 60 | 1.4627 |
| 1.8907 | 5.63 | 70 | 1.4151 |
| 1.9159 | 6.43 | 80 | 1.3653 |
| 1.7551 | 7.24 | 90 | 1.3158 |
| 1.7168 | 8.04 | 100 | 1.2606 |
| 1.5976 | 8.84 | 110 | 1.2106 |
| 1.4944 | 9.65 | 120 | 1.1602 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Library
- transformers
- Type
- pegasus
- Created
- Aug 24, 2023
- Updated
- Aug 24, 2023