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Bart_classifier
zera09/Bart_classifier
Bart_classifier is a machine learning model from zera09. 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
- May 26, 2024
- Updated
- May 26, 2024
- SHA
- d0218a64
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_classifier
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: 0.5262
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2135 | 1.0 | 219 | 0.1489 |
| 0.197 | 2.0 | 438 | 0.2690 |
| 0.1443 | 3.0 | 657 | 0.1525 |
| 0.1655 | 4.0 | 876 | 0.1819 |
| 0.0984 | 5.0 | 1095 | 0.1819 |
| 0.0854 | 6.0 | 1314 | 0.2220 |
| 0.0622 | 7.0 | 1533 | 0.2892 |
| 0.0446 | 8.0 | 1752 | 0.3801 |
| 0.0171 | 9.0 | 1971 | 0.4832 |
| 0.0108 | 10.0 | 2190 | 0.5262 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- May 26, 2024
- Updated
- May 26, 2024