Downloads · 30 days
7
13% of all-time downloads
t5-base-cnn-dm-on-2000-news
imsumit18/t5-base-cnn-dm-on-2000-news
t5-base-cnn-dm-on-2000-news is a machine learning model from imsumit18. 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
53
Public
Parameters
223M
3.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors892 MB · 100%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Mar 7, 2024
- Updated
- Mar 7, 2024
- SHA
- 17dd289d
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. -->
t5-base-cnn-dm-on-2000-news
This model is a fine-tuned version of flax-community/t5-base-cnn-dm on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6098
- Rouge1: 40.1108
- Rouge2: 35.0247
- Rougel: 39.2043
- Rougelsum: 39.4272
- 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: 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 | 211 | 0.8550 | 33.8522 | 24.4634 | 31.5244 | 32.1795 | 19.0 |
| No log | 2.0 | 422 | 0.6559 | 36.5992 | 28.76 | 34.8508 | 35.3186 | 19.0 |
| 0.9852 | 3.0 | 633 | 0.5826 | 38.1153 | 31.7278 | 36.8636 | 37.0955 | 19.0 |
| 0.9852 | 4.0 | 844 | 0.5637 | 38.3865 | 32.5346 | 37.1463 | 37.5175 | 19.0 |
| 0.3875 | 5.0 | 1055 | 0.5694 | 39.6094 | 33.9914 | 38.4403 | 38.6466 | 19.0 |
| 0.3875 | 6.0 | 1266 | 0.5727 | 39.7837 | 34.2137 | 38.6669 | 38.9124 | 19.0 |
| 0.3875 | 7.0 | 1477 | 0.5813 | 39.9572 | 34.6307 | 38.885 | 39.1153 | 19.0 |
| 0.207 | 8.0 | 1688 | 0.5934 | 39.867 | 34.7336 | 38.941 | 39.1977 | 19.0 |
| 0.207 | 9.0 | 1899 | 0.6053 | 40.0643 | 34.9731 | 39.1287 | 39.3602 | 19.0 |
| 0.138 | 10.0 | 2110 | 0.6098 | 40.1108 | 35.0247 | 39.2043 | 39.4272 | 19.0 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Mar 7, 2024
- Updated
- Mar 7, 2024