fix losses
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@@ -251,7 +251,7 @@ class TestCustomOptimizers(unittest.TestCase):
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"adapter": "lora",
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"adapter": "lora",
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"lora_r": 8,
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"lora_r": 8,
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"lora_alpha": 16,
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"lora_dropout": 0.0,
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"lora_target_linear": True,
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"lora_target_linear": True,
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"val_set_size": 0.1,
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"val_set_size": 0.1,
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"special_tokens": {
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"special_tokens": {
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@@ -264,18 +264,22 @@ class TestCustomOptimizers(unittest.TestCase):
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},
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},
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],
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],
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"num_epochs": 1,
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"num_epochs": 1,
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"sample_packing": True,
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"pad_to_sequence_len": True,
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"micro_batch_size": 8,
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"micro_batch_size": 8,
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"gradient_accumulation_steps": 1,
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"gradient_accumulation_steps": 1,
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"output_dir": temp_dir,
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"output_dir": temp_dir,
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"learning_rate": 2e-4,
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"learning_rate": 1e-4,
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"optimizer": "came_pytorch",
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"optimizer": "came_pytorch",
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"adam_beta3": 0.9999,
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"adam_beta3": 0.9999,
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"adam_epsilon2": 1e-16,
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"adam_epsilon2": 1e-16,
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"max_steps": 50,
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"max_steps": 80,
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"warmup_steps": 5,
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"logging_steps": 1,
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"logging_steps": 1,
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"lr_scheduler": "cosine",
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"lr_scheduler": "cosine",
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"save_first_step": False,
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"save_first_step": False,
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"use_tensorboard": True,
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"use_tensorboard": True,
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"seed": 42,
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}
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}
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)
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)
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@@ -287,10 +291,10 @@ class TestCustomOptimizers(unittest.TestCase):
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check_model_output_exists(temp_dir, cfg)
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check_model_output_exists(temp_dir, cfg)
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check_tensorboard_loss_decreased(
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check_tensorboard_loss_decreased(
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temp_dir + "/runs",
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temp_dir + "/runs",
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initial_window=5,
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initial_window=10,
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final_window=5,
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final_window=10,
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max_initial=4.5,
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max_initial=4.0,
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max_final=4.3,
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max_final=3.0,
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)
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)
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