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my_awesome_billsum_model
roequitz/my_awesome_billsum_model
my_awesome_billsum_model is a machine learning model from roequitz. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- May 28, 2024
- Updated
- May 28, 2024
- SHA
- 26c4c942
Base models
Datasets
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. -->
my_awesome_billsum_model
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the dialogstudio dataset. It achieves the following results on the evaluation set:
- Loss: 1.9811
- Rouge1: 0.4187
- Rouge2: 0.1911
- Rougel: 0.3373
- Rougelsum: 0.338
- Gen Len: 65.1636
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 55 | 2.0591 | 0.4232 | 0.1899 | 0.3412 | 0.342 | 64.8545 |
| No log | 2.0 | 110 | 1.9802 | 0.4125 | 0.19 | 0.3329 | 0.3334 | 66.7545 |
| No log | 3.0 | 165 | 1.9671 | 0.4172 | 0.1927 | 0.3348 | 0.3357 | 65.3545 |
| No log | 4.0 | 220 | 1.9811 | 0.4187 | 0.1911 | 0.3373 | 0.338 | 65.1636 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- May 28, 2024
- Updated
- May 28, 2024