model_24
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: 0.6165
- eval_accuracy: 0.7775
- eval_precision: 0.7770
- eval_recall: 0.7775
- eval_f1: 0.7771
- eval_runtime: 42.58
- eval_samples_per_second: 287.576
- eval_steps_per_second: 17.99
- epoch: 27.0
- step: 82674
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 60
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.03
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
distilbert/distilbert-base-uncased