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distilbert-base-uncased-lora-text-classification
sidd272/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from sidd272. 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 Sep 24, 2023
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Sep 24, 2023
- Updated
- Sep 24, 2023
- SHA
- e547dabb
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 the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8488
- Accuracy: {'accuracy': 0.8924438393464942}
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 |
|---|---|---|---|---|
| 0.4284 | 1.0 | 1469 | 0.6122 | {'accuracy': 0.8515997277059224} |
| 0.318 | 2.0 | 2938 | 0.4710 | {'accuracy': 0.8686181075561606} |
| 0.3091 | 3.0 | 4407 | 0.3991 | {'accuracy': 0.8910823689584751} |
| 0.267 | 4.0 | 5876 | 0.3609 | {'accuracy': 0.9081007488087134} |
| 0.2111 | 5.0 | 7345 | 0.5392 | {'accuracy': 0.8876786929884275} |
| 0.2231 | 6.0 | 8814 | 0.6888 | {'accuracy': 0.8978897208985704} |
| 0.1116 | 7.0 | 10283 | 0.6468 | {'accuracy': 0.8965282505105514} |
| 0.1111 | 8.0 | 11752 | 0.8718 | {'accuracy': 0.8849557522123894} |
| 0.076 | 9.0 | 13221 | 0.8075 | {'accuracy': 0.8965282505105514} |
| 0.0672 | 10.0 | 14690 | 0.8488 | {'accuracy': 0.8924438393464942} |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- License
- apache-2.0
- Created
- Sep 24, 2023
- Updated
- Sep 24, 2023