80 lines
4.2 KiB
YAML
80 lines
4.2 KiB
YAML
# LoRA Fine-tuning Configuration for Sanskrit Translation & Transliteration Enhancement
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base_model: Qwen/Qwen2.5-7B-Instruct
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# Use our custom chat template
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chat_template_jinja: "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a Sanskrit-English bilingual AI assistant created by Divax Shah (diabolic6045). You are specialized in Sanskrit language understanding and translation.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a Sanskrit-English bilingual AI assistant created by Divax Shah (diabolic6045). You are specialized in Sanskrit language understanding and translation.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\\\"name\\\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}"
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datasets:
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- path: diabolic6045/Sanskrit-transliteration-chat-dataset
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type: chat_template
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field_messages: messages
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message_property_mappings:
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role: role
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content: content
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roles:
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system:
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- system
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user:
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- user
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assistant:
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- assistant
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val_set_size: 0.1
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output_dir: ./outputs/sanskrit-chat-7b-lora
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# LoRA configuration
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adapter: lora
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lora_model_dir:
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sequence_len: 512
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sample_packing: true
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eval_sample_packing: true
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# LoRA hyperparameters
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lora_r: 16
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lora_alpha: 32
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lora_dropout: 0.05
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lora_target_modules:
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- gate_proj
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- down_proj
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- up_proj
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- q_proj
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- v_proj
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- k_proj
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- o_proj
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gradient_accumulation_steps: 4
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micro_batch_size: 2
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num_epochs: 3
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optimizer: adamw_8bit
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lr_scheduler: cosine
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learning_rate: 0.00002
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# Precision configuration
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bf16: auto
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tf32: false
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# Memory optimization
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gradient_checkpointing: true
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flash_attention: true
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# Training schedule
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warmup_ratio: 0.1
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evals_per_epoch: 4
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saves_per_epoch: 1
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weight_decay: 0.0
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logging_steps: 1
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# Wandb configuration
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wandb_project: sanskrit-qwen
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wandb_entity:
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wandb_watch:
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wandb_name: sanskrit-qwen-7b-lora-chat
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wandb_log_model:
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# Resume from checkpoint
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resume_from_checkpoint:
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# Hub model ID (update with your username)
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# hub_model_id: your-username/Sanskrit-Qwen2.5-7B-LoRA-chat
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