bert-base-uncased-finetuned-best
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.4101
- Matthews Correlation: 0.6094
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: 2.9901559201237305e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- 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 | Matthews Correlation |
---|---|---|---|---|
No log | 1.0 | 268 | 0.4389 | 0.5041 |
0.3831 | 2.0 | 536 | 0.4101 | 0.6094 |
0.3831 | 3.0 | 804 | 0.5908 | 0.5854 |
0.1334 | 4.0 | 1072 | 0.7048 | 0.6012 |
0.1334 | 5.0 | 1340 | 0.7637 | 0.5809 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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Dataset used to train cansurav/bert-base-uncased-finetuned-best
Evaluation results
- Matthews Correlation on gluevalidation set self-reported0.609