Downloads · 30 days
7
15% of all-time downloads
bart-large-cnn-finetuned-roundup-8
theojolliffe/bart-large-cnn-finetuned-roundup-8
bart-large-cnn-finetuned-roundup-8 is a machine learning model from theojolliffe. 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
46
Public
Repo size
4.9 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.6 GB · 100%
At a glance
- Library
- transformers
- License
- mit
- Model type
- bart
- Access
- Public
- Created
- May 3, 2022
- Updated
- May 3, 2022
- SHA
- 4f19c59d
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-large-cnn-finetuned-roundup-8
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4519
- Rouge1: 49.5671
- Rouge2: 27.0118
- Rougel: 30.8538
- Rougelsum: 45.5503
- Gen Len: 141.75
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 132 | 1.3159 | 48.5275 | 28.0817 | 30.6646 | 45.5024 | 142.0 |
| No log | 2.0 | 264 | 1.2377 | 47.0791 | 27.4386 | 28.9458 | 44.1536 | 142.0 |
| No log | 3.0 | 396 | 1.2474 | 49.3567 | 29.5904 | 30.8029 | 46.6083 | 142.0 |
| 0.9623 | 4.0 | 528 | 1.2914 | 47.8795 | 27.0611 | 29.8538 | 44.4494 | 142.0 |
| 0.9623 | 5.0 | 660 | 1.2982 | 49.9921 | 28.4839 | 31.5688 | 46.9734 | 142.0 |
| 0.9623 | 6.0 | 792 | 1.3521 | 46.7269 | 25.8672 | 29.7325 | 43.8279 | 142.0 |
| 0.9623 | 7.0 | 924 | 1.4102 | 47.4995 | 26.0066 | 29.4342 | 44.1102 | 141.8 |
| 0.3734 | 8.0 | 1056 | 1.4519 | 49.5671 | 27.0118 | 30.8538 | 45.5503 | 141.75 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
- Library
- transformers
- Type
- bart
- License
- mit
- Created
- May 3, 2022
- Updated
- May 3, 2022