Downloads · 30 days
5
9% of all-time downloads
finetuned_pegasus_custom
Glow-01/finetuned_pegasus_custom
finetuned_pegasus_custom is a machine learning model from Glow-01. 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.
should probably proofread and complete it, then remove this comment. --
All-time downloads
55
Public
Parameters
571M
2.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors2.3 GB · 100%
At a glance
- Library
- transformers
- Model type
- pegasus
- Access
- Public
- Created
- Mar 11, 2024
- Updated
- Mar 11, 2024
- SHA
- 46ee7e3e
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. -->
finetuned_pegasus_custom
This model is a fine-tuned version of google/pegasus-multi_news on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5792
- Rouge1: 43.3499
- Rouge2: 19.473
- Rougel: 28.3372
- Rougelsum: 39.6698
- Gen Len: 167.2593
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 0.98 | 31 | 1.6733 | 45.2908 | 20.6545 | 28.8174 | 41.1913 | 157.2593 |
| No log | 2.0 | 63 | 1.6448 | 45.8258 | 20.4208 | 29.3649 | 41.4304 | 164.7778 |
| No log | 2.98 | 94 | 1.6308 | 45.6111 | 20.1988 | 28.7912 | 41.5061 | 157.8519 |
| No log | 4.0 | 126 | 1.6105 | 45.2388 | 20.9335 | 28.8736 | 41.3696 | 160.6667 |
| No log | 4.98 | 157 | 1.6009 | 44.84 | 20.5064 | 29.3276 | 40.9796 | 154.0741 |
| No log | 6.0 | 189 | 1.5903 | 44.3777 | 19.987 | 29.5859 | 40.7764 | 163.1111 |
| No log | 6.98 | 220 | 1.5844 | 44.3786 | 20.2566 | 29.1194 | 40.9269 | 160.1111 |
| No log | 8.0 | 252 | 1.5821 | 43.3413 | 19.3 | 28.3204 | 39.619 | 153.6667 |
| No log | 8.98 | 283 | 1.5796 | 42.9684 | 18.9515 | 27.909 | 39.166 | 162.1852 |
| No log | 9.84 | 310 | 1.5792 | 43.3499 | 19.473 | 28.3372 | 39.6698 | 167.2593 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
- Library
- transformers
- Type
- pegasus
- Created
- Mar 11, 2024
- Updated
- Mar 11, 2024