Downloads · 30 days
7
2% of all-time downloads
led-base-16384-finetuned-cnn_dailymail
CyrexPro/led-base-16384-finetuned-cnn_dailymail
led-base-16384-finetuned-cnn_dailymail is a machine learning model from CyrexPro. 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
461
Public
Parameters
162M
37.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin648 MB · 50%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- led
- Access
- Public
- Created
- Aug 12, 2023
- Updated
- May 9, 2024
- SHA
- 069cbf7a
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. -->
led-base-16384-finetuned-cnn_dailymail
This model is a fine-tuned version of allenai/led-base-16384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0670
- Rouge1: 26.5966
- Rouge2: 13.4937
- Rougel: 22.1204
- Rougelsum: 25.0057
- Bleu 1: 4.81
- Bleu 2: 3.2976
- Bleu 3: 2.4273
- Meteor: 13.4385
- Lungime rezumat: 12.5033
- Lungime original: 48.674
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: 5.6e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Lungime rezumat | Lungime original |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.1488 | 1.0 | 7165 | 1.0638 | 26.6263 | 13.2802 | 22.0654 | 25.0416 | 4.7464 | 3.1681 | 2.2958 | 13.3027 | 12.5003 | 48.674 |
| 0.9202 | 2.0 | 14330 | 1.0475 | 26.5843 | 13.4795 | 22.083 | 25.0206 | 4.7096 | 3.1931 | 2.3493 | 13.3342 | 12.4533 | 48.674 |
| 0.7778 | 3.0 | 21495 | 1.0465 | 26.5754 | 13.4585 | 22.0522 | 24.9943 | 4.729 | 3.2152 | 2.3491 | 13.3759 | 12.455 | 48.674 |
| 0.6729 | 4.0 | 28660 | 1.0670 | 26.5966 | 13.4937 | 22.1204 | 25.0057 | 4.81 | 3.2976 | 2.4273 | 13.4385 | 12.5033 | 48.674 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- led
- License
- apache-2.0
- Created
- Aug 12, 2023
- Updated
- May 9, 2024