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Trained model with classification head weights
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metadata
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: defect-classification-llama-baseline-25-epochs-MAIL-15
    results: []

defect-classification-llama-baseline-25-epochs-MAIL-15

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2285
  • Accuracy: 0.9239

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: 1536
  • eval_batch_size: 1536
  • 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: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.4712 1.0 354 1.3872 0.7466
0.944 2.0 708 0.9087 0.7794
0.7409 3.0 1062 0.7188 0.8174
0.6044 4.0 1416 0.5781 0.8373
0.5294 5.0 1770 0.5239 0.8371
0.4728 6.0 2124 0.4699 0.8534
0.4288 7.0 2478 0.4105 0.8686
0.4065 8.0 2832 0.3832 0.8753
0.3705 9.0 3186 0.3526 0.8822
0.3441 10.0 3540 0.3338 0.8938
0.332 11.0 3894 0.3195 0.8949
0.3188 12.0 4248 0.2982 0.9029
0.3093 13.0 4602 0.2908 0.9041
0.2831 14.0 4956 0.2835 0.9056
0.2764 15.0 5310 0.2697 0.9114
0.2689 16.0 5664 0.2679 0.9114
0.2618 17.0 6018 0.2623 0.9159
0.2568 18.0 6372 0.2589 0.9108
0.2533 19.0 6726 0.2474 0.9156
0.2497 20.0 7080 0.2438 0.9164
0.2428 21.0 7434 0.2393 0.9203
0.2402 22.0 7788 0.2330 0.9223
0.236 23.0 8142 0.2323 0.9230
0.2359 24.0 8496 0.2297 0.9235
0.2342 25.0 8850 0.2285 0.9239

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0