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distilbert-base-uncased-lora-text-classification
lennon2020/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from lennon2020. 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
- May 21, 2024
- Updated
- May 21, 2024
- SHA
- 98f9ade3
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: 2.0657
- Accuracy: {'accuracy': 0.7330827067669173}
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 |
|---|---|---|---|---|
| 0.9636 | 1.0 | 538 | 0.8582 | {'accuracy': 0.6992481203007519} |
| 0.7447 | 2.0 | 1076 | 1.0010 | {'accuracy': 0.7030075187969925} |
| 0.5876 | 3.0 | 1614 | 0.9129 | {'accuracy': 0.7142857142857143} |
| 0.4728 | 4.0 | 2152 | 1.1641 | {'accuracy': 0.7255639097744361} |
| 0.4145 | 5.0 | 2690 | 1.3646 | {'accuracy': 0.7330827067669173} |
| 0.2917 | 6.0 | 3228 | 1.4447 | {'accuracy': 0.7556390977443609} |
| 0.2485 | 7.0 | 3766 | 1.7574 | {'accuracy': 0.7330827067669173} |
| 0.1596 | 8.0 | 4304 | 1.9367 | {'accuracy': 0.7330827067669173} |
| 0.1468 | 9.0 | 4842 | 2.0091 | {'accuracy': 0.7368421052631579} |
| 0.1128 | 10.0 | 5380 | 2.0657 | {'accuracy': 0.7330827067669173} |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- May 21, 2024
- Updated
- May 21, 2024