more train steps
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@@ -33,7 +33,7 @@ class TestMixtral(unittest.TestCase):
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"adapter": "qlora",
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"lora_r": 16,
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"lora_alpha": 32,
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"lora_dropout": 0.1,
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"lora_dropout": 0.0,
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"lora_target_linear": True,
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"val_set_size": 0.05,
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"special_tokens": {},
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@@ -47,16 +47,18 @@ class TestMixtral(unittest.TestCase):
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"micro_batch_size": 4,
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"gradient_accumulation_steps": 1,
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"output_dir": temp_dir,
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"learning_rate": 2e-4,
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"learning_rate": 3e-3,
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"optimizer": "adamw_bnb_8bit",
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"lr_scheduler": "cosine",
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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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"save_steps": 50,
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"eval_steps": 50,
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"save_steps": 80,
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"eval_steps": 80,
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"bf16": "auto",
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"save_first_step": False,
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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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cfg = validate_config(cfg)
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@@ -67,8 +69,8 @@ class TestMixtral(unittest.TestCase):
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check_model_output_exists(temp_dir, cfg)
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check_tensorboard_loss_decreased(
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temp_dir + "/runs",
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initial_window=5,
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final_window=5,
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initial_window=10,
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final_window=10,
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max_initial=6.0,
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max_final=4.7,
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)
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@@ -93,16 +95,18 @@ class TestMixtral(unittest.TestCase):
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"micro_batch_size": 4,
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"gradient_accumulation_steps": 1,
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"output_dir": temp_dir,
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"learning_rate": 2e-4,
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"optimizer": "adamw_bnb_8bit",
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"learning_rate": 5e-4,
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"optimizer": "adamw_torch_fused",
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"lr_scheduler": "cosine",
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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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"save_steps": 50,
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"eval_steps": 50,
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"save_steps": 80,
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"eval_steps": 80,
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"bf16": "auto",
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"save_first_step": False,
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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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cfg = validate_config(cfg)
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