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bart-noised-with-all-dist
gayanin/bart-noised-with-all-dist
bart-noised-with-all-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 5, 2024
- Updated
- Feb 5, 2024
- SHA
- e2707deb
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-all-dist
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: 0.5751
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 |
|---|---|---|---|
| 0.7697 | 0.11 | 500 | 0.7542 |
| 0.8211 | 0.21 | 1000 | 0.7434 |
| 0.7764 | 0.32 | 1500 | 0.6996 |
| 0.7867 | 0.43 | 2000 | 0.6640 |
| 0.6795 | 0.54 | 2500 | 0.6581 |
| 0.6778 | 0.64 | 3000 | 0.6535 |
| 0.7028 | 0.75 | 3500 | 0.6547 |
| 0.7104 | 0.86 | 4000 | 0.6318 |
| 0.7032 | 0.96 | 4500 | 0.6213 |
| 0.6062 | 1.07 | 5000 | 0.6157 |
| 0.5789 | 1.18 | 5500 | 0.6175 |
| 0.5689 | 1.28 | 6000 | 0.6118 |
| 0.5183 | 1.39 | 6500 | 0.6147 |
| 0.5834 | 1.5 | 7000 | 0.5938 |
| 0.5708 | 1.61 | 7500 | 0.5964 |
| 0.5118 | 1.71 | 8000 | 0.5924 |
| 0.5284 | 1.82 | 8500 | 0.5900 |
| 0.5192 | 1.93 | 9000 | 0.5936 |
| 0.5358 | 2.03 | 9500 | 0.5879 |
| 0.4422 | 2.14 | 10000 | 0.5948 |
| 0.4852 | 2.25 | 10500 | 0.5917 |
| 0.4383 | 2.35 | 11000 | 0.5847 |
| 0.552 | 2.46 | 11500 | 0.5824 |
| 0.4464 | 2.57 | 12000 | 0.5810 |
| 0.4089 | 2.68 | 12500 | 0.5793 |
| 0.4898 | 2.78 | 13000 | 0.5749 |
| 0.4753 | 2.89 | 13500 | 0.5794 |
| 0.4579 | 3.0 | 14000 | 0.5751 |
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 5, 2024
- Updated
- Feb 5, 2024