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distilbert-base-uncased-lora-text-classification
MomoSen/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from MomoSen. 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
- Mar 7, 2024
- Updated
- Mar 7, 2024
- SHA
- d36f5dbc
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. -->
distilbert-base-uncased-lora-text-classification
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: 0.9904
- Accuracy: {'accuracy': 0.899}
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.5709 | {'accuracy': 0.837} |
| 0.4386 | 2.0 | 500 | 0.4510 | {'accuracy': 0.871} |
| 0.4386 | 3.0 | 750 | 0.6571 | {'accuracy': 0.887} |
| 0.1891 | 4.0 | 1000 | 0.6197 | {'accuracy': 0.894} |
| 0.1891 | 5.0 | 1250 | 0.7688 | {'accuracy': 0.897} |
| 0.0683 | 6.0 | 1500 | 0.8231 | {'accuracy': 0.892} |
| 0.0683 | 7.0 | 1750 | 0.8949 | {'accuracy': 0.901} |
| 0.0136 | 8.0 | 2000 | 0.9553 | {'accuracy': 0.896} |
| 0.0136 | 9.0 | 2250 | 1.0202 | {'accuracy': 0.892} |
| 0.0067 | 10.0 | 2500 | 0.9904 | {'accuracy': 0.899} |
Framework versions
- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.15.2
- Library
- peft
- License
- apache-2.0
- Created
- Mar 7, 2024
- Updated
- Mar 7, 2024