simplify the example configs to be more minimal and less daunting (#2486) [skip ci]
* simplify the example configs to be more minimal and less daunting * drop empty s2_attention from example yamls
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@@ -5,9 +5,6 @@ model_type: GPTNeoXForCausalLM
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tokenizer_type: AutoTokenizer
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# Automatically upload checkpoint and final model to HF
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# hub_model_id: username/custom_model_name
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load_in_8bit: false
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load_in_4bit: false
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gptq: false
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device_map: auto
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datasets:
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@@ -22,7 +19,6 @@ max_packed_sequence_len: 2048
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lora_r: 64
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lora_alpha: 32
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lora_dropout: 0.0
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lora_target_modules:
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lora_target_linear: true
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lora_fan_in_fan_out: true # pythia/GPTNeoX lora specific
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wandb_project:
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@@ -37,16 +33,10 @@ num_epochs: 5
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learning_rate: 0.00003
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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train_on_inputs: false
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group_by_length: false
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bf16: false
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fp16: false
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float16: true
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tf32: true
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flash_optimum: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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gradient_checkpointing: true
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fsdp:
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fsdp_config:
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