training
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 3.6940
- eval_accuracy: 0.5030
- eval_f1: 0.4903
- eval_precision: 0.5068
- eval_recall: 0.5030
- eval_runtime: 1.2509
- eval_samples_per_second: 262.212
- eval_steps_per_second: 13.59
- epoch: 5.09
- step: 336
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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 11
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for davidgaofc/ShadowAttackF
Base model
distilbert/distilbert-base-uncased