v12p_deberta-base-finetuned-mrpc
This model is a fine-tuned version of microsoft/deberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3430
- Accuracy: 0.8897
- F1: 0.9223
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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 56
- 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 | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 115 | 0.4883 | 0.7672 | 0.8490 |
No log | 2.0 | 230 | 0.3899 | 0.8186 | 0.8806 |
No log | 3.0 | 345 | 0.3016 | 0.8799 | 0.9130 |
No log | 4.0 | 460 | 0.3280 | 0.8799 | 0.9114 |
0.403 | 5.0 | 575 | 0.3430 | 0.8897 | 0.9223 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.13.3
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