bertiny-finetuned-finer
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the finer-139 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0882
- Precision: 0.5339
- Recall: 0.0360
- F1: 0.0675
- Accuracy: 0.9847
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
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0871 | 1.0 | 11255 | 0.0952 | 0.0 | 0.0 | 0.0 | 0.9843 |
0.0864 | 2.0 | 22510 | 0.0895 | 0.7640 | 0.0082 | 0.0162 | 0.9844 |
0.0929 | 3.0 | 33765 | 0.0882 | 0.5339 | 0.0360 | 0.0675 | 0.9847 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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Model tree for muhtasham/bert-tiny-finetuned-finer
Base model
google/bert_uncased_L-2_H-128_A-2Dataset used to train muhtasham/bert-tiny-finetuned-finer
Evaluation results
- Precision on finer-139self-reported0.534
- Recall on finer-139self-reported0.036
- F1 on finer-139self-reported0.067
- Accuracy on finer-139self-reported0.985