squeezebert-uncased-finetuned-mrpc
This model is a fine-tuned version of squeezebert/squeezebert-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.4261
- Accuracy: 0.8137
- F1: 0.8733
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: 32
- eval_batch_size: 32
- seed: 24
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 115 | 0.5015 | 0.7843 | 0.8603 |
| No log | 2.0 | 230 | 0.4571 | 0.7941 | 0.8627 |
| No log | 3.0 | 345 | 0.4261 | 0.8137 | 0.8733 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Dataset used to train VitaliiVrublevskyi/squeezebert-uncased-finetuned-mrpc
Evaluation results
- Accuracy on gluevalidation set self-reported0.814
- F1 on gluevalidation set self-reported0.873