(self, tokenizer, model, use_question_stance_approach=True, learning_rate=1e-3)
| 14 | class NaiveSeqClassModule(pl.LightningModule): |
| 15 | # Instantiate the model |
| 16 | def __init__(self, tokenizer, model, use_question_stance_approach=True, learning_rate=1e-3): |
| 17 | super().__init__() |
| 18 | self.tokenizer = tokenizer |
| 19 | self.model = model |
| 20 | self.learning_rate = learning_rate |
| 21 | |
| 22 | self.train_acc = torchmetrics.Accuracy() |
| 23 | self.val_acc = torchmetrics.Accuracy() |
| 24 | self.test_acc = torchmetrics.Accuracy() |
| 25 | |
| 26 | self.train_f1 = F1Score(num_classes=4, average="macro") |
| 27 | self.val_f1 = F1Score(num_classes=4, average=None) |
| 28 | self.test_f1 = F1Score(num_classes=4, average=None) |
| 29 | |
| 30 | self.use_question_stance_approach = use_question_stance_approach |
| 31 | |
| 32 | |
| 33 | # Do a forward pass through the model |
nothing calls this directly
no outgoing calls
no test coverage detected