AdditiveLLM
Collection
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Updated
defect-classification-distilbert-prompt-05-epochs
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3165
- Accuracy: 0.8563
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: 2e-05
- train_batch_size: 2048
- eval_batch_size: 2048
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3534 | 1.0 | 19907 | 0.3347 | 0.8548 |
| 0.2855 | 2.0 | 39814 | 0.3274 | 0.8521 |
| 0.3284 | 3.0 | 59721 | 0.3146 | 0.8588 |
| 0.2881 | 4.0 | 79628 | 0.3177 | 0.8560 |
| 0.2813 | 5.0 | 99535 | 0.3165 | 0.8563 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
Inference Providers
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This model is not currently available via any of the supported third-party Inference Providers, and
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Model tree for ppak10/defect-classification-distilbert-prompt-05-epochs
Base model
distilbert/distilbert-base-uncased