my_awesome_wnut_model2

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my_awesome_wnut_model2

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

• eval_loss: 0.1068
• eval_precision: 0.55
• eval_recall: 0.3587
• eval_f1: 0.4342
• eval_accuracy: 0.9605
• eval_runtime: 4.4133
• eval_samples_per_second: 35.574
• eval_steps_per_second: 2.266
• epoch: 2.0
• step: 92

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cpu
• Datasets 2.18.0
• Tokenizers 0.15.2