Downloads · 30 days
5
20% of all-time downloads
my_awesome_billsum_model
sjung/my_awesome_billsum_model
my_awesome_billsum_model is a machine learning model from sjung. 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. --
All-time downloads
25
Public
Parameters
60.5M
242 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors242 MB · 99%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Nov 14, 2023
- Updated
- Nov 14, 2023
- SHA
- 0a9084c8
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 t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.5213
- Rouge1: 0.1408
- Rouge2: 0.0553
- Rougel: 0.1179
- Rougelsum: 0.118
- Gen Len: 19.0
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 | 62 | 2.8080 | 0.1287 | 0.0386 | 0.1085 | 0.1088 | 19.0 |
| No log | 2.0 | 124 | 2.6015 | 0.1375 | 0.05 | 0.1156 | 0.1157 | 19.0 |
| No log | 3.0 | 186 | 2.5384 | 0.1417 | 0.0569 | 0.119 | 0.1192 | 19.0 |
| No log | 4.0 | 248 | 2.5213 | 0.1408 | 0.0553 | 0.1179 | 0.118 | 19.0 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Nov 14, 2023
- Updated
- Nov 14, 2023