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bart-large-cnn-finetuned-roundup-3-2
theojolliffe/bart-large-cnn-finetuned-roundup-3-2
bart-large-cnn-finetuned-roundup-3-2 is a machine learning model from theojolliffe. 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
- bart
- Access
- Public
- Created
- May 5, 2022
- Updated
- May 5, 2022
- SHA
- 5ac8bb9f
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. -->
bart-large-cnn-finetuned-roundup-3-2
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2234
- Rouge1: 50.9324
- Rouge2: 30.5257
- Rougel: 32.2166
- Rougelsum: 47.9849
- Gen Len: 141.6562
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 258 | 1.2775 | 50.0638 | 30.3036 | 32.9555 | 47.3277 | 142.0 |
| 1.1818 | 2.0 | 516 | 1.2234 | 50.9324 | 30.5257 | 32.2166 | 47.9849 | 141.6562 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
- Library
- transformers
- Type
- bart
- License
- mit
- Created
- May 5, 2022
- Updated
- May 5, 2022