my_awesome_wnut_model
This model is a fine-tuned version of distilbert-base-uncased on the shipping_label_ner dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0550
- eval_precision: 0.9286
- eval_recall: 0.9630
- eval_f1: 0.9455
- eval_accuracy: 0.9904
- eval_runtime: 0.046
- eval_samples_per_second: 108.697
- eval_steps_per_second: 21.739
- epoch: 55.0
- step: 110
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for jarvisx17/my_awesome_wnut_model
Base model
distilbert/distilbert-base-uncased