Downloads · 30 days
5
28% of all-time downloads
my_longer_summarization_model
iamj33l/my_longer_summarization_model
my_longer_summarization_model is a machine learning model from iamj33l. 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
18
Public
Parameters
60.5M
727 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
- Oct 3, 2024
- Updated
- Oct 3, 2024
- SHA
- 0b06a354
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_longer_summarization_model
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2700
- Rouge1: 0.4373
- Rouge2: 0.1851
- Rougel: 0.2845
- Rougelsum: 0.284
- Gen Len: 249.996
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: 8
- eval_batch_size: 8
- 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 | 124 | 2.4805 | 0.4073 | 0.1571 | 0.2477 | 0.248 | 225.7621 |
| No log | 2.0 | 248 | 2.4026 | 0.4211 | 0.1683 | 0.2619 | 0.2617 | 228.9919 |
| No log | 3.0 | 372 | 2.3562 | 0.4247 | 0.1736 | 0.2731 | 0.273 | 243.871 |
| No log | 4.0 | 496 | 2.3316 | 0.432 | 0.1782 | 0.2774 | 0.277 | 248.7419 |
| 2.688 | 5.0 | 620 | 2.3041 | 0.4264 | 0.1744 | 0.2781 | 0.2778 | 250.8065 |
| 2.688 | 6.0 | 744 | 2.2914 | 0.4289 | 0.1781 | 0.2808 | 0.2805 | 248.375 |
| 2.688 | 7.0 | 868 | 2.2820 | 0.4305 | 0.1797 | 0.2831 | 0.2827 | 249.8871 |
| 2.688 | 8.0 | 992 | 2.2765 | 0.4337 | 0.1824 | 0.2827 | 0.2822 | 249.246 |
| 2.5114 | 9.0 | 1116 | 2.2719 | 0.4338 | 0.1819 | 0.2837 | 0.2832 | 249.379 |
| 2.5114 | 10.0 | 1240 | 2.2700 | 0.4373 | 0.1851 | 0.2845 | 0.284 | 249.996 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Oct 3, 2024
- Updated
- Oct 3, 2024