unified_skill_ner

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unified_skill_ner

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0048
• eval_Profession-B-f1: 0.9781
• eval_Profession-I-f1: 0.9798
• eval_Loc-B-f1: 0.9792
• eval_Loc-I-f1: 0.9804
• eval_AreaSkill-B-f1: 0.9625
• eval_AreaSkill-I-f1: 0.9264
• eval_Language-B-f1: 0.9976
• eval_Language-I-f1: 0
• eval_CertificatesLicense-B-f1: 0.9818
• eval_CertificatesLicense-I-f1: 1.0
• eval_Driverslicense-B-f1: 0.9912
• eval_Driverslicense-I-f1: 1.0
• eval_f1: 0.9409
• eval_runtime: 10.5223
• eval_samples_per_second: 490.958
• eval_steps_per_second: 61.394
• 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: 4e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 123
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2