distilbert-base-uncased-finetuned-LIAR
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.5162
- eval_precision: 0.5364
- eval_recall: 0.5283
- eval_f1: 0.5301
- eval_accuracy: 0.5283
- eval_runtime: 30.6964
- eval_samples_per_second: 97.731
- eval_steps_per_second: 3.062
- step: 0
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Framework versions
- Transformers 4.28.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.13.3
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