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roberta-base-lora-text-classification
tparng/roberta-base-lora-text-classification
roberta-base-lora-text-classification is a machine learning model from tparng. 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 mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Nov 22, 2023
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At a glance
- License
- mit
- Access
- Public
- Created
- Nov 22, 2023
- Updated
- Nov 22, 2023
- SHA
- e1ebce01
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. -->
roberta-base-lora-text-classification
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7451
- Accuracy: {'accuracy': 0.933}
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 | 0.3071 | {'accuracy': 0.919} |
| 0.3665 | 2.0 | 500 | 0.3954 | {'accuracy': 0.922} |
| 0.3665 | 3.0 | 750 | 0.3318 | {'accuracy': 0.937} |
| 0.1483 | 4.0 | 1000 | 0.5179 | {'accuracy': 0.942} |
| 0.1483 | 5.0 | 1250 | 0.5112 | {'accuracy': 0.933} |
| 0.0829 | 6.0 | 1500 | 0.5775 | {'accuracy': 0.936} |
| 0.0829 | 7.0 | 1750 | 0.6473 | {'accuracy': 0.931} |
| 0.019 | 8.0 | 2000 | 0.6950 | {'accuracy': 0.937} |
| 0.019 | 9.0 | 2250 | 0.7328 | {'accuracy': 0.931} |
| 0.008 | 10.0 | 2500 | 0.7451 | {'accuracy': 0.933} |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- mit
- Created
- Nov 22, 2023
- Updated
- Nov 22, 2023