bert-concat-2-finetune-simcse-truncate

This model was trained from scratch on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 3.7771

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: 0.0005
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 1000
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
5.7122	0.25	1000	4.7219
4.8805	0.5	2000	4.1641
4.3911	0.76	3000	3.7771

Framework versions

• Transformers 4.26.1
• Pytorch 1.11.0+cu113
• Datasets 2.13.0
• Tokenizers 0.13.3