bert-base-cased-finetuned-wls-manual-5ep

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

• Loss: 1.3713

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss
2.1603	0.93	7	1.8523
1.6398	2.0	15	1.6332
1.5675	2.93	22	1.5257
1.4167	4.0	30	1.4623
1.3885	4.67	35	1.4795

Framework versions

• Transformers 4.31.0
• Pytorch 1.11.0+cu113
• Datasets 2.14.4
• Tokenizers 0.13.3