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mbart-large-50-headline-base
mdosama39/mbart-large-50-headline-base
mbart-large-50-headline-base is a machine learning model from mdosama39. 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. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- mbart
- Access
- Public
- Created
- May 17, 2024
- Updated
- May 17, 2024
- SHA
- b011be96
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. -->
mbart-large-50-headline-base
This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3895
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 16.4913
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.5021 | 1.0 | 202 | 2.2386 | 0.0 | 0.0 | 0.0 | 0.0 | 18.5533 |
| 1.5996 | 2.0 | 404 | 2.0142 | 0.0 | 0.0 | 0.0 | 0.0 | 16.5261 |
| 0.991 | 3.0 | 606 | 2.1117 | 0.0 | 0.0 | 0.0 | 0.0 | 16.0968 |
| 0.2882 | 4.0 | 808 | 2.3895 | 0.0 | 0.0 | 0.0 | 0.0 | 16.4913 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- transformers
- Type
- mbart
- License
- mit
- Created
- May 17, 2024
- Updated
- May 17, 2024