trainerL

This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.8068
• eval_precision: 0.8217
• eval_recall: 0.8168
• eval_f1: 0.8162
• eval_accuracy: 0.8168
• eval_runtime: 58.8181
• eval_samples_per_second: 9.283
• eval_steps_per_second: 1.173
• epoch: 1.23
• step: 420

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-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Framework versions

• Transformers 4.39.1
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2