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reverted automatically disabling split loss calc, since it seems that it's actually cacling loss on prom causes the oddities, maybe

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mrq 2024-06-01 12:34:59 -05:00
parent 8cf176ab46
commit c1fcd889d5
2 changed files with 2 additions and 2 deletions
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2
vall_e/config.py
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@ -213,7 +213,7 @@ class Model:
attention: str = "auto" attention: str = "auto"
audio_embedding_sums: bool = True audio_embedding_sums: bool = True
dropout: float = 0.1 # adjustable dropout value dropout: float = 0.1 # adjustable dropout value
loss_factors: dict = field(default_factory=lambda: {}) # "text": 0.1, "prom": 0.0, "resp": 1.0 }) loss_factors: dict = field(default_factory=lambda: { "text": 0.1, "prom": 0.0, "resp": 1.0 })
kv_heads: int = 0 kv_heads: int = 0
def get(self, name=None): def get(self, name=None):

2
vall_e/utils/trainer.py
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@ -162,7 +162,7 @@ def train(
#batch = to_device(batch, torch.cuda.current_device()) #batch = to_device(batch, torch.cuda.current_device())
stats = engines.step(batch=batch, feeder=train_feeder) stats = engines.step(batch=batch, feeder=train_feeder)
stats['epoch'] = engines.global_samples / len(train_dl.dataset.paths) stats['epoch'] = engines.global_samples / len(train_dl.dataset.paths) * world_size()
""" """
stats['batch'] = { stats['batch'] = {