nmb-paperspace-hf/bert-base-uncased-go_emotions

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bert-base-uncased-go_emotions

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

• —Loss: 0.1095
• —Roc Auc: 0.8084

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: 0.0002
• —trainbatchsize: 2
• —evalbatchsize: 4
• —seed: 42
• —distributed_type: IPU
• —gradientaccumulationsteps: 39
• —totaltrainbatch_size: 2496
• —totalevalbatch_size: 256
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 5
• —training precision: Mixed Precision

Training results

Framework versions

• —Transformers 4.25.1
• —Pytorch 1.13.1+cpu
• —Datasets 2.11.0
• —Tokenizers 0.13.3