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bart-noised-with-gcd-dist
gayanin/bart-noised-with-gcd-dist
bart-noised-with-gcd-dist is a machine learning model from gayanin. 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. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- Feb 4, 2024
- Updated
- Feb 5, 2024
- SHA
- c1df50a3
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-noised-with-gcd-dist
This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4647
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9409 | 0.11 | 500 | 0.7734 |
| 0.7621 | 0.21 | 1000 | 0.6828 |
| 0.7451 | 0.32 | 1500 | 0.6330 |
| 0.7254 | 0.43 | 2000 | 0.6034 |
| 0.5801 | 0.54 | 2500 | 0.5854 |
| 0.6766 | 0.64 | 3000 | 0.5649 |
| 0.6162 | 0.75 | 3500 | 0.5493 |
| 0.6187 | 0.86 | 4000 | 0.5316 |
| 0.6053 | 0.96 | 4500 | 0.5221 |
| 0.4931 | 1.07 | 5000 | 0.5193 |
| 0.5096 | 1.18 | 5500 | 0.5153 |
| 0.5142 | 1.28 | 6000 | 0.5149 |
| 0.4612 | 1.39 | 6500 | 0.5045 |
| 0.5176 | 1.5 | 7000 | 0.4971 |
| 0.426 | 1.61 | 7500 | 0.4986 |
| 0.4537 | 1.71 | 8000 | 0.4890 |
| 0.5026 | 1.82 | 8500 | 0.4809 |
| 0.4392 | 1.93 | 9000 | 0.4773 |
| 0.408 | 2.03 | 9500 | 0.4818 |
| 0.3796 | 2.14 | 10000 | 0.4778 |
| 0.3643 | 2.25 | 10500 | 0.4792 |
| 0.3717 | 2.35 | 11000 | 0.4770 |
| 0.3817 | 2.46 | 11500 | 0.4703 |
| 0.3765 | 2.57 | 12000 | 0.4662 |
| 0.3783 | 2.68 | 12500 | 0.4663 |
| 0.3463 | 2.78 | 13000 | 0.4652 |
| 0.3931 | 2.89 | 13500 | 0.4649 |
| 0.4079 | 3.0 | 14000 | 0.4647 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Feb 4, 2024
- Updated
- Feb 5, 2024