OptimizerArgs

config_hub/finetune/falcon-7b/lora.yaml

@@ -84,18 +84,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights. (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.0003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.0
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -122,3 +110,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95

config_hub/finetune/falcon-7b/qlora.yaml

@@ -86,18 +86,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.0003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.0
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -124,3 +112,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95

config_hub/finetune/gemma-2b/full.yaml

@@ -55,18 +55,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights. (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.0003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.0
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -93,3 +81,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95

config_hub/finetune/gemma-2b/lora.yaml

@@ -85,18 +85,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights. (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.0003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.2
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -123,3 +111,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95

config_hub/finetune/gemma-2b/qlora.yaml

@@ -85,18 +85,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights. (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.0003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.0
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -123,3 +111,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95

config_hub/finetune/gemma-7b/lora.yaml

@@ -85,18 +85,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights. (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.0003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.0
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -123,3 +111,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95

config_hub/finetune/gemma-7b/qlora.yaml

@@ -85,18 +85,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights. (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.0003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.0
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -123,3 +111,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95

config_hub/finetune/llama-2-7b/full.yaml

@@ -58,18 +58,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights. (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.1
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -96,3 +84,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95

config_hub/finetune/llama-2-7b/lora.yaml

@@ -84,18 +84,6 @@ train:
   # Whether to tie the embedding weights with the language modeling head weights. (type: Optional[bool], default: null)
   tie_embeddings:
 
-  #   (type: float, default: 0.0003)
-  learning_rate: 0.0002
-
-  #   (type: float, default: 0.02)
-  weight_decay: 0.0
-
-  #   (type: float, default: 0.9)
-  beta1: 0.9
-
-  #   (type: float, default: 0.95)
-  beta2: 0.95
-
   #   (type: Optional[float], default: null)
   max_norm:
 
@@ -122,3 +110,21 @@ logger_name: csv
 
 # The random seed to use for reproducibility. (type: int, default: 1337)
 seed: 1337
+
+# Optimizer-related arguments
+optimizer:
+
+  class_path: torch.optim.AdamW
+
+  init_args:
+
+    #   (type: float, default: 0.001)
+    lr: 0.0002
+
+    #   (type: float, default: 0.01)
+    weight_decay: 0.0
+
+    #   (type: tuple, default: (0.9,0.999))
+    betas:
+      - 0.9
+      - 0.95