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my_awesome_billsum_model_32
limaatulya/my_awesome_billsum_model_32
my_awesome_billsum_model_32 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
- 64ea1644
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_32
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: 0.6953
- Rouge1: 0.9328
- Rouge2: 0.7819
- Rougel: 0.8546
- Rougelsum: 0.857
- Gen Len: 5.2083
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 | 2.1371 | 0.3875 | 0.2627 | 0.3679 | 0.3672 | 17.5625 |
| No log | 2.0 | 24 | 1.6293 | 0.4137 | 0.286 | 0.3928 | 0.3924 | 16.5625 |
| No log | 3.0 | 36 | 1.1556 | 0.478 | 0.347 | 0.4538 | 0.4505 | 14.6458 |
| No log | 4.0 | 48 | 0.8702 | 0.7792 | 0.6558 | 0.7344 | 0.7311 | 8.2708 |
| No log | 5.0 | 60 | 0.7539 | 0.9328 | 0.7819 | 0.8546 | 0.857 | 5.2083 |
| No log | 6.0 | 72 | 0.7230 | 0.9328 | 0.7819 | 0.8546 | 0.857 | 5.2083 |
| No log | 7.0 | 84 | 0.7094 | 0.9328 | 0.7819 | 0.8546 | 0.857 | 5.2083 |
| No log | 8.0 | 96 | 0.7026 | 0.9328 | 0.7819 | 0.8546 | 0.857 | 5.2083 |
| No log | 9.0 | 108 | 0.6978 | 0.9328 | 0.7819 | 0.8546 | 0.857 | 5.2083 |
| No log | 10.0 | 120 | 0.6953 | 0.9328 | 0.7819 | 0.8546 | 0.857 | 5.2083 |
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