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distilbert-base-uncased-lora-text-classification
smend0/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from smend0. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Jan 25, 2024
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jan 25, 2024
- Updated
- Jan 25, 2024
- SHA
- 2ccbd59b
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 a truncated IMDB dataset. It achieves the following results on the evaluation set:
- Loss: 1.7208
- Accuracy: {'accuracy': 0.876}
Model description
The purpose of this model is to turn distilbert into a sentiment classification model.
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 2.0890 | {'accuracy': 0.862} |
| 0.2005 | 2.0 | 500 | 1.8919 | {'accuracy': 0.874} |
| 0.2005 | 3.0 | 750 | 1.7205 | {'accuracy': 0.871} |
| 0.0963 | 4.0 | 1000 | 1.7208 | {'accuracy': 0.876} |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.1
- License
- apache-2.0
- Created
- Jan 25, 2024
- Updated
- Jan 25, 2024