distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of distilbert-base-uncased on the conll2003 dataset. It achieves the following results on the evaluation set:
- eval_loss: 2.3520
- eval_precision: 0.0251
- eval_recall: 0.1595
- eval_f1: 0.0434
- eval_accuracy: 0.0530
- eval_runtime: 12.1709
- eval_samples_per_second: 267.031
- eval_steps_per_second: 16.761
- 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: 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: 3
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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Model tree for vincenzodeleo/distilbert-base-uncased-finetuned-ner
Base model
distilbert/distilbert-base-uncased