bert-base-uncased-finetuned-sdg-Mar23

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: 0.3234
• Acc: 0.9113

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

##Labelling 0:'1', 1:'10', 2:'11', 3:'12', 4:'13', 5:'14', 6:'15', 7:'16', 8:'2', 9:'3', 10:'4', 11:'5', 12:'6', 13:'7', 14:'8', 15:'9'

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Acc
0.4165	1.0	1098	0.3656	0.8908
0.2062	2.0	2196	0.3234	0.9113

Framework versions

• Transformers 4.27.1
• Pytorch 1.12.0a0+8a1a93a
• Datasets 2.10.1
• Tokenizers 0.13.2