feat: pythia 12b train

configs/train/finetune_pythia.yaml

@@ -0,0 +1,33 @@
+# model/tokenizer
+model_name: "EleutherAI/pythia-12b"
+tokenizer_name: "EleutherAI/pythia-12b"
+gradient_checkpointing: true
+save_name: "nomic-ai/gpt4all-delphi"
+
+# dataset
+streaming: false
+num_proc: 64
+dataset_path: "nomic-ai/gpt4all-j-prompt-generations"
+revision: "v1.3-groovy"
+max_length: 1024
+batch_size: 16
+
+# train dynamics
+lr: 2.0e-5
+min_lr: 0 
+weight_decay: 0.0
+eval_every: 500
+save_every: 500
+log_grads_every: 100
+output_dir: ckpts/pythia/
+checkpoint: null
+lora: false
+warmup_steps: 500
+num_epochs: 3 
+
+# logging
+wandb: true
+wandb_entity: gpt4all
+wandb_project_name: gpt4all
+seed: 42
+

data.py

@@ -72,7 +72,9 @@ def load_data(config, tokenizer):
         dataset = load_dataset("json", data_files=files, split="train")
 
     else:
-        dataset = load_dataset(dataset_path, split="train")
+        dataset = load_dataset(dataset_path,
+                               split="train",
+                               revision=config["revision"] if "revision" in config else None)
 
     dataset = dataset.train_test_split(test_size=.05, seed=config["seed"])
 
@@ -87,13 +89,13 @@ def load_data(config, tokenizer):
     train_dataset = train_dataset.map(
         lambda ele: tokenize_inputs(config, tokenizer, ele),
         batched=True,
-        remove_columns=["source", "prompt"],
+        remove_columns=["source", "prompt", "id"],
         **kwargs
     )
     val_dataset = val_dataset.map(
         lambda ele: tokenize_inputs(config, tokenizer, ele),
         batched=True,
-        remove_columns=["source", "prompt"],
+        remove_columns=["source", "prompt", "id"],
         **kwargs
     )