Downloads · 30 days
7
23% of all-time downloads
bart-base-luong
ntluongg/bart-base-luong
bart-base-luong is a machine learning model from ntluongg. 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
31
Public
Parameters
139M
558 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors558 MB · 99%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- Jun 17, 2024
- Updated
- Jun 17, 2024
- SHA
- 07b041f1
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. -->
bart-base-luong
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2356
- Rouge1: 45.4069
- Rouge2: 23.2838
- Rougel: 39.4615
- Rougelsum: 41.5905
- Gen Len: 18.0
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: 1e-05
- 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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.2702 | 1.0 | 2307 | 0.2429 | 43.0834 | 19.6597 | 36.4303 | 39.1751 | 18.0 |
| 0.2121 | 2.0 | 4615 | 0.2338 | 43.5038 | 20.3513 | 37.1389 | 39.418 | 18.0 |
| 0.1917 | 3.0 | 6922 | 0.2327 | 44.3658 | 21.3002 | 38.0506 | 40.4574 | 18.0 |
| 0.1768 | 4.0 | 9230 | 0.2304 | 44.761 | 22.2373 | 38.713 | 40.955 | 18.0 |
| 0.1658 | 5.0 | 11537 | 0.2310 | 45.176 | 22.8385 | 39.0963 | 41.2373 | 18.0 |
| 0.1567 | 6.0 | 13845 | 0.2327 | 45.2475 | 22.7529 | 38.9987 | 41.2975 | 18.0 |
| 0.1498 | 7.0 | 16152 | 0.2350 | 45.4093 | 22.9187 | 39.1624 | 41.4173 | 18.0 |
| 0.1444 | 8.0 | 18460 | 0.2340 | 45.6332 | 23.1632 | 39.5567 | 41.5893 | 18.0 |
| 0.1406 | 9.0 | 20767 | 0.2353 | 45.1827 | 22.7108 | 39.089 | 41.2022 | 18.0 |
| 0.1385 | 10.0 | 23070 | 0.2356 | 45.4069 | 23.2838 | 39.4615 | 41.5905 | 18.0 |
Framework versions
- Transformers 4.36.1
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Jun 17, 2024
- Updated
- Jun 17, 2024