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my_awesome_billsum_model_36
limaatulya/my_awesome_billsum_model_36
my_awesome_billsum_model_36 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 20, 2024
- Updated
- Jun 20, 2024
- SHA
- 490e55d7
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_36
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: 0.4601
- Rouge1: 0.9721
- Rouge2: 0.8819
- Rougel: 0.9256
- Rougelsum: 0.9271
- Gen Len: 4.9167
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 | 1.9874 | 0.4145 | 0.2913 | 0.3883 | 0.3891 | 17.6042 |
| No log | 2.0 | 24 | 1.4300 | 0.4322 | 0.3091 | 0.4061 | 0.4068 | 17.0833 |
| No log | 3.0 | 36 | 0.9451 | 0.5076 | 0.3886 | 0.4814 | 0.48 | 14.75 |
| No log | 4.0 | 48 | 0.6345 | 0.8401 | 0.7297 | 0.7858 | 0.7884 | 7.625 |
| No log | 5.0 | 60 | 0.5226 | 0.9591 | 0.8586 | 0.8998 | 0.9042 | 5.125 |
| No log | 6.0 | 72 | 0.4907 | 0.9701 | 0.8736 | 0.9129 | 0.9167 | 4.8958 |
| No log | 7.0 | 84 | 0.4783 | 0.9701 | 0.8736 | 0.9129 | 0.9167 | 4.8958 |
| No log | 8.0 | 96 | 0.4697 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 |
| No log | 9.0 | 108 | 0.4627 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 |
| No log | 10.0 | 120 | 0.4601 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 |
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 20, 2024
- Updated
- Jun 20, 2024