NLP_sequence_clasiffication
This model is a fine-tuned version of distilroberta-base on the glue and the mrpc datasets. It achieves the following results on the evaluation set:
- Loss: 0.5325
- Accuracy: 0.8505
- F1: 0.8872
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: 5e-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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5129 | 1.09 | 500 | 0.7246 | 0.8113 | 0.8679 |
| 0.3526 | 2.18 | 1000 | 0.5325 | 0.8505 | 0.8872 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.13.3
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Dataset used to train deathperminutV2/NLP_sequence_clasiffication
Evaluation results
- Accuracy on gluevalidation set self-reported0.850
- F1 on gluevalidation set self-reported0.887