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my_awesome_billsum_model_12
limaatulya/my_awesome_billsum_model_12
my_awesome_billsum_model_12 is a machine learning model from limaatulya. 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
- t5
- Access
- Public
- Created
- Jun 18, 2024
- Updated
- Jun 18, 2024
- SHA
- 8b096af0
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. -->
my_awesome_billsum_model_12
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6167
- Rouge1: 0.9635
- Rouge2: 0.8396
- Rougel: 0.8914
- Rougelsum: 0.8919
- Gen Len: 5.1042
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 12 | 2.0578 | 0.4077 | 0.2938 | 0.3916 | 0.3923 | 17.6458 |
| No log | 2.0 | 24 | 1.5690 | 0.4152 | 0.2977 | 0.4017 | 0.4017 | 17.3125 |
| No log | 3.0 | 36 | 1.1237 | 0.47 | 0.3505 | 0.4472 | 0.4469 | 15.4792 |
| No log | 4.0 | 48 | 0.8172 | 0.7763 | 0.6588 | 0.7333 | 0.7354 | 8.8542 |
| No log | 5.0 | 60 | 0.6854 | 0.9174 | 0.7868 | 0.8455 | 0.8454 | 6.0833 |
| No log | 6.0 | 72 | 0.6514 | 0.9635 | 0.8396 | 0.8914 | 0.8919 | 5.1042 |
| No log | 7.0 | 84 | 0.6364 | 0.9635 | 0.8396 | 0.8914 | 0.8919 | 5.1042 |
| No log | 8.0 | 96 | 0.6261 | 0.9635 | 0.8396 | 0.8914 | 0.8919 | 5.1042 |
| No log | 9.0 | 108 | 0.6202 | 0.9635 | 0.8396 | 0.8914 | 0.8919 | 5.1042 |
| No log | 10.0 | 120 | 0.6167 | 0.9635 | 0.8396 | 0.8914 | 0.8919 | 5.1042 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jun 18, 2024
- Updated
- Jun 18, 2024