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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
