Finetuned-model-on-custom-dataset-700k
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: 0.1560
- eval_accuracy: 0.9363
- eval_f1: 0.9368
- eval_precision: 0.9381
- eval_recall: 0.9363
- eval_validation_accuracy: 0.9363
- eval_runtime: 592.0773
- eval_samples_per_second: 236.456
- eval_steps_per_second: 2.464
- epoch: 2.0
- step: 11668
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: 5e-06
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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