Downloads · 30 days
18
10% of all-time downloads
mBART-TextSimp-LT-BatchSize8-lr1e-4
eglkan1/mBART-TextSimp-LT-BatchSize8-lr1e-4
mBART-TextSimp-LT-BatchSize8-lr1e-4 is a machine learning model from eglkan1. 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 mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
172
Public
Repo size
24.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin2.4 GB · 100%
At a glance
- Library
- transformers
- License
- mit
- Model type
- mbart
- Access
- Public
- Created
- Apr 11, 2024
- Updated
- Jul 19, 2024
- SHA
- f8354658
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. -->
mBART-TextSimp-LT-BatchSize8-lr1e-4
This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0744
- Rouge1: 0.7931
- Rouge2: 0.657
- Rougel: 0.7873
- Sacrebleu: 56.7266
- Gen Len: 34.9093
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 5.5149 | 1.0 | 104 | 3.9238 | 0.6383 | 0.4681 | 0.6268 | 40.2914 | 36.6301 |
| 0.0989 | 2.0 | 209 | 0.0807 | 0.6925 | 0.5318 | 0.6852 | 46.8337 | 34.9093 |
| 0.0666 | 3.0 | 313 | 0.0679 | 0.7014 | 0.5448 | 0.6936 | 47.4249 | 34.9093 |
| 0.0464 | 4.0 | 418 | 0.0765 | 0.698 | 0.5344 | 0.6859 | 46.7217 | 34.9093 |
| 0.0344 | 5.0 | 522 | 0.0668 | 0.7604 | 0.6085 | 0.7526 | 49.5391 | 34.9117 |
| 0.0168 | 6.0 | 627 | 0.0652 | 0.7825 | 0.6391 | 0.7763 | 53.7888 | 34.9093 |
| 0.0116 | 7.0 | 731 | 0.0674 | 0.7911 | 0.6558 | 0.7856 | 55.8977 | 34.9093 |
| 0.0036 | 7.96 | 832 | 0.0744 | 0.7931 | 0.657 | 0.7873 | 56.7266 | 34.9093 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.4
- Tokenizers 0.13.3
- Library
- transformers
- Type
- mbart
- License
- mit
- Created
- Apr 11, 2024
- Updated
- Jul 19, 2024