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
• train_batch_size: 2
• eval_batch_size: 4
• seed: 42
• distributed_type: IPU
• gradient_accumulation_steps: 39
• total_train_batch_size: 2496
• total_eval_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
• lr_scheduler_type: cosine
• lr_scheduler_warmup_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