test_twowayloss_implementation

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 8.9001
• Accuracy: 0.5659
• Precision: 0.0114
• Recall: 0.5082
• F1: 0.0223
• Hamming: 0.4341

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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Hamming
8.8818	0.0	5	8.9210	0.5632	0.0110	0.4947	0.0216	0.4368
8.124	0.0	10	8.9001	0.5659	0.0114	0.5082	0.0223	0.4341

Framework versions

• Transformers 4.35.0.dev0
• Pytorch 2.0.1+cu118
• Datasets 2.7.1
• Tokenizers 0.14.1