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Updated README with Labelling (#1)
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: bert-base-uncased-finetuned-sdg-Mar23
    results: []

bert-base-uncased-finetuned-sdg-Mar23

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

  • Loss: 0.3234
  • Acc: 0.9113

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

##Labelling 0:'1', 1:'10', 2:'11', 3:'12', 4:'13', 5:'14', 6:'15', 7:'16', 8:'2', 9:'3', 10:'4', 11:'5', 12:'6', 13:'7', 14:'8', 15:'9'

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Acc
0.4165 1.0 1098 0.3656 0.8908
0.2062 2.0 2196 0.3234 0.9113

Framework versions

  • Transformers 4.27.1
  • Pytorch 1.12.0a0+8a1a93a
  • Datasets 2.10.1
  • Tokenizers 0.13.2