bert_uncased_tiny_2xthicc-multi-emails-hq

bert_uncased_L-4_H-128_A-2-mlm-multi-emails-hq

This model is a fine-tuned version of google/bert_uncased_L-4_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.8524
• Accuracy: 0.5077

Model description

Double the layers of BERT-tiny, fine-tuned on email data for eight epochs.

Intended uses & limitations

• This is primarily an example/test

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0003
• train_batch_size: 8
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 8.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 2.0.0.dev20230129+cu118
• Datasets 2.8.0
• Tokenizers 0.13.1