NLP_model_test
This model is a fine-tuned version of distilroberta-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6241
- Accuracy: 0.6838
- F1: 0.8122
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: 0.0002
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.659 | 1.09 | 500 | 0.6391 | 0.6838 | 0.8122 |
| 0.6404 | 2.18 | 1000 | 0.6258 | 0.6838 | 0.8122 |
| 0.6392 | 3.27 | 1500 | 0.6269 | 0.6838 | 0.8122 |
| 0.6416 | 4.36 | 2000 | 0.6241 | 0.6838 | 0.8122 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for jessjmr/NLP_model_test
Base model
distilbert/distilroberta-baseDataset used to train jessjmr/NLP_model_test
Evaluation results
- Accuracy on gluevalidation set self-reported0.684
- F1 on gluevalidation set self-reported0.812