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ft_cls_bert
prakhartrivedi/ft_cls_bert
ft_cls_bert is a machine learning model from prakhartrivedi. 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 peft. 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
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Apr 17, 2025
- Updated
- Apr 17, 2025
- SHA
- 7480a59c
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. -->
ft_cls_bert
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1077
- Accuracy: {'accuracy': 0.884}
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.6258 | {'accuracy': 0.85} |
| 0.4254 | 2.0 | 500 | 0.4517 | {'accuracy': 0.873} |
| 0.4254 | 3.0 | 750 | 0.6362 | {'accuracy': 0.879} |
| 0.1683 | 4.0 | 1000 | 0.8084 | {'accuracy': 0.876} |
| 0.1683 | 5.0 | 1250 | 0.9185 | {'accuracy': 0.883} |
| 0.0519 | 6.0 | 1500 | 0.9096 | {'accuracy': 0.887} |
| 0.0519 | 7.0 | 1750 | 1.0121 | {'accuracy': 0.881} |
| 0.0116 | 8.0 | 2000 | 1.0798 | {'accuracy': 0.882} |
| 0.0116 | 9.0 | 2250 | 1.1104 | {'accuracy': 0.884} |
| 0.0101 | 10.0 | 2500 | 1.1077 | {'accuracy': 0.884} |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.2
- Pytorch 2.6.0
- Datasets 3.5.0
- Tokenizers 0.21.1
- Library
- peft
- License
- apache-2.0
- Created
- Apr 17, 2025
- Updated
- Apr 17, 2025