| Dummy Model for Lab4 |
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| This model is a fine-tuned version of bert-base-uncased on SST-2 dataset. |
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| Results of the evaluation set: |
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| Accuracy: 0.64 |
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| This model was fine-tuneded for personal research usage. |
| with randomly selected 100 training datas and 100 evaluation datas from SST-2 dataset. |
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| # Evaluation |
| import evaluate |
| predictions = trainer.predict(Resrt_eval) |
| print(predictions.predictions.shape, predictions.label_ids.shape) |
| preds = np.argmax(predictions.predictions, axis=-1) |
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| metric = evaluate.load("glue", "sst2") |
| metric.compute(predictions=preds, references=predictions.label_ids) |
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| Training hyperparameters |
| The following hyperparameters were used during training: |
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| learning_rate: unset |
| train_batch_size: unset |
| eval_batch_size: unset |
| seed of training dataset: 49282927487 |
| seed of evaluation dataset:492829487 |
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| lr_scheduler_type: linear |
| num_epochs: 3.0 |
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| Training results |
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