AdditiveLLM
Collection
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Updated
defect-classification-distilbert-baseline-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: 0.3466
- Accuracy: 0.8406
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: 512
- eval_batch_size: 512
- 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 |
|---|---|---|---|---|
| 0.6532 | 1.0 | 1062 | 0.5593 | 0.7704 |
| 0.5415 | 2.0 | 2124 | 0.4230 | 0.8107 |
| 0.5135 | 3.0 | 3186 | 0.3803 | 0.8271 |
| 0.5031 | 4.0 | 4248 | 0.3597 | 0.8346 |
| 0.4909 | 5.0 | 5310 | 0.3466 | 0.8406 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no pipeline_tag.
Model tree for ppak10/defect-classification-distilbert-baseline-05-epochs
Base model
distilbert/distilbert-base-uncased