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roberta-base-ner-conll2003 – AI Model by andi611 | AlphaNeural AI

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andi611/
roberta-base-ner-conll2003

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-base-ner

This model is a fine-tuned version of roberta-base on the conll2003 dataset. It achieves the following results on the evaluation set:

eval_loss: 0.0814
eval_precision: 0.9101
eval_recall: 0.9336
eval_f1: 0.9217
eval_accuracy: 0.9799
eval_runtime: 10.2964
eval_samples_per_second: 315.646
eval_steps_per_second: 39.529
epoch: 1.14
step: 500

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: 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: 4.0

Framework versions

Transformers 4.8.2
Pytorch 1.8.1+cu111
Datasets 1.8.0
Tokenizers 0.10.3