NTCAL/norbert2_sentiment_norec_to_gpu_3000_rader

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norbert2sentimentnorecengpu3000rader

This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 1.4721
• —Compute Metrics: :
• —Accuracy: 0.69
• —Balanced Accuracy: 0.5
• —F1 Score: 0.8166
• —Recall: 1.0
• —Precision: 0.69

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
• —trainbatchsize: 1
• —evalbatchsize: 1
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 2

Training results

Framework versions

• —Transformers 4.26.0
• —Pytorch 1.13.1+cu117
• —Datasets 2.9.0
• —Tokenizers 0.13.2