keep only a single bash script

peft/fft.sh

@@ -1,22 +0,0 @@
-#!/bin/bash
-
-export TF_CPP_MIN_LOG_LEVEL=2 XLA_PYTHON_CLIENT_PREALLOCATE=false
-
-python3 finetune.py \
-    --model-name="google/timesfm-1.0-200m" \
-    --backend="gpu" \
-    --horizon-len=128 \
-    --context-len=512 \
-    --freq="15min" \
-    --data-path="../datasets/ETT-small/ETTm1.csv" \
-    --num-epochs=1 \
-    --learning-rate=1e-3 \
-    --adam-epsilon=1e-7 \
-    --adam-clip-threshold=1e2 \
-    --early-stop-patience=10 \
-    --datetime-col="date" \
-    --boundaries=34560 46080 57600 \
-    --cos-initial-decay-value=1e-4 \
-    --cos-decay-steps=40000 \
-    --cos-final-decay-value=1e-5 \
-    --ema-decay=0.9999

peft/finetune.py

@@ -62,12 +62,12 @@ RANDOM_SEED = 1234
 
 def finetune(
     *,
-    checkpoint_path: Annotated[
-        str, typer.Option(help="The path to the model checkpoint.")
-    ] = None,
     model_name: Annotated[
         str, typer.Option(help="Specify the name of the huggingface model.")
     ] = "google/timesfm-1.0-200m",
+    checkpoint_path: Annotated[
+        str, typer.Option(help="The path to the local model checkpoint.")
+    ] = None,
     datetime_col: Annotated[str, typer.Option(help="Column having datetime.")] = "ds",
     ts_cols: Annotated[
         list[str], typer.Option(help="Columns of time-series features.")
@@ -115,7 +115,7 @@ def finetune(
     use_lora: Annotated[
         bool,
         typer.Option(
-            help="Train low rank adapters. Freeze all other params in model",
+            help="Train low rank adapters for stacked transformer block",
         ),
     ] = False,
     lora_rank: Annotated[
@@ -126,7 +126,9 @@ def finetune(
     ] = 8,
     lora_target_modules: Annotated[
         str,
-        typer.Option(help="LoRA target modules. Allowed values: [all, attention, mlp]"),
+        typer.Option(
+            help="LoRA target modules of the transformer block. Allowed values: [all, attention, mlp]"
+        ),
     ] = "all",
     use_dora: Annotated[
         bool,
@@ -137,7 +139,7 @@ def finetune(
     use_linear_probing: Annotated[
         bool,
         typer.Option(
-            help="Linear Probing. Train only input/output and embedding params. Freeze params in self attention modules.",
+            help="Linear Probing. Train only input/output and embedding params. Freeze params in stack transformer block.",
         ),
     ] = False,
     checkpoint_dir: Annotated[

peft/finetune.sh

@@ -1,10 +1,13 @@
 #!/bin/bash
 
+# Script to finetune a model with specific configurations
+# Adjust the parameters below as needed. For a full list of options and descriptions, run the script with the --help flag.
+
 export TF_CPP_MIN_LOG_LEVEL=2 XLA_PYTHON_CLIENT_PREALLOCATE=false
 
 python3 finetune.py \
     --model-name="google/timesfm-1.0-200m" \
-    --backend="gpu" \
+    --backend="cpu" \
     --horizon-len=128 \
     --context-len=512 \
     --freq="15min" \
@@ -15,7 +18,6 @@ python3 finetune.py \
     --adam-clip-threshold=1e2 \
     --early-stop-patience=10 \
     --datetime-col="date" \
-    --boundaries=34560 46080 57600 \
     --use-lora \
     --lora-rank=1 \
     --lora-target-modules="all" \
@@ -23,4 +25,7 @@ python3 finetune.py \
     --cos-initial-decay-value=1e-4 \
     --cos-decay-steps=40000 \
     --cos-final-decay-value=1e-5 \
-    --ema-decay=0.9999
+    --ema-decay=0.9999
+
+# To see all available options and their descriptions, use the --help flag
+# python3 finetune.py --help

peft/linear_probing.sh

@@ -1,23 +0,0 @@
-#!/bin/bash
-
-export TF_CPP_MIN_LOG_LEVEL=2 XLA_PYTHON_CLIENT_PREALLOCATE=false
-
-python3 finetune.py \
-    --model-name="google/timesfm-1.0-200m" \
-    --backend="gpu" \
-    --horizon-len=128 \
-    --context-len=512 \
-    --freq="15min" \
-    --data-path="../datasets/ETT-small/ETTm1.csv" \
-    --num-epochs=100 \
-    --learning-rate=1e-2 \
-    --adam-epsilon=1e-7 \
-    --adam-clip-threshold=1e2 \
-    --early-stop-patience=10 \
-    --datetime-col="date" \
-    --boundaries=1000 46080 57600 \
-    --use-linear-probing \
-    --cos-initial-decay-value=1e-4 \
-    --cos-decay-steps=40000 \
-    --cos-final-decay-value=1e-5 \
-    --ema-decay=0.9999

peft/lora.sh

@@ -1,25 +0,0 @@
-#!/bin/bash
-
-export TF_CPP_MIN_LOG_LEVEL=2 XLA_PYTHON_CLIENT_PREALLOCATE=false
-
-python3 finetune.py \
-    --model-name="google/timesfm-1.0-200m" \
-    --backend="gpu" \
-    --horizon-len=128 \
-    --context-len=512 \
-    --freq="15min" \
-    --data-path="../datasets/ETT-small/ETTm1.csv" \
-    --num-epochs=100 \
-    --learning-rate=1e-3 \
-    --adam-epsilon=1e-7 \
-    --adam-clip-threshold=1e2 \
-    --early-stop-patience=10 \
-    --datetime-col="date" \
-    --boundaries=34560 46080 57600 \
-    --use-lora \
-    --lora-rank=1 \
-    --lora-target-modules="all" \
-    --cos-initial-decay-value=1e-4 \
-    --cos-decay-steps=40000 \
-    --cos-final-decay-value=1e-5 \
-    --ema-decay=0.9999