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  1. calibration/llama3.2-1b-instruct/banking77/size=256/seed=0/bias_shift/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261211.gamma.1527988.0 +3 -0
  2. calibration/llama3.2-1b-instruct/banking77/size=256/seed=0/bias_shift/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  3. calibration/llama3.2-1b-instruct/banking77/size=256/seed=0/dp_calibration/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261178.gamma.1527584.0 +3 -0
  4. calibration/llama3.2-1b-instruct/banking77/size=256/seed=0/dp_calibration/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  5. calibration/llama3.2-1b-instruct/banking77/size=256/seed=0/temp_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261190.gamma.1527714.0 +3 -0
  6. calibration/llama3.2-1b-instruct/banking77/size=256/seed=0/temp_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  7. calibration/llama3.2-1b-instruct/banking77/size=256/seed=0/vector_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261199.gamma.1527843.0 +3 -0
  8. calibration/llama3.2-1b-instruct/banking77/size=256/seed=0/vector_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  9. calibration/llama3.2-1b-instruct/banking77/size=256/seed=1/bias_shift/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261257.gamma.1528522.0 +3 -0
  10. calibration/llama3.2-1b-instruct/banking77/size=256/seed=1/bias_shift/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  11. calibration/llama3.2-1b-instruct/banking77/size=256/seed=1/dp_calibration/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261223.gamma.1528143.0 +3 -0
  12. calibration/llama3.2-1b-instruct/banking77/size=256/seed=1/dp_calibration/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  13. calibration/llama3.2-1b-instruct/banking77/size=256/seed=1/temp_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261236.gamma.1528279.0 +3 -0
  14. calibration/llama3.2-1b-instruct/banking77/size=256/seed=1/temp_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  15. calibration/llama3.2-1b-instruct/banking77/size=256/seed=1/vector_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261245.gamma.1528408.0 +3 -0
  16. calibration/llama3.2-1b-instruct/banking77/size=256/seed=1/vector_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  17. calibration/llama3.2-1b-instruct/banking77/size=256/seed=2/bias_shift/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261303.gamma.1529078.0 +3 -0
  18. calibration/llama3.2-1b-instruct/banking77/size=256/seed=2/bias_shift/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  19. calibration/llama3.2-1b-instruct/banking77/size=256/seed=2/temp_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261283.gamma.1528829.0 +3 -0
  20. calibration/llama3.2-1b-instruct/banking77/size=256/seed=2/temp_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  21. calibration/llama3.2-1b-instruct/banking77/size=256/seed=2/vector_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261291.gamma.1528960.0 +3 -0
  22. calibration/llama3.2-1b-instruct/banking77/size=256/seed=3/bias_shift/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261349.gamma.1529627.0 +3 -0
  23. calibration/llama3.2-1b-instruct/banking77/size=256/seed=3/bias_shift/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  24. calibration/llama3.2-1b-instruct/banking77/size=256/seed=3/dp_calibration/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261315.gamma.1529208.0 +3 -0
  25. calibration/llama3.2-1b-instruct/banking77/size=256/seed=3/dp_calibration/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  26. calibration/llama3.2-1b-instruct/banking77/size=256/seed=3/temp_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261328.gamma.1529365.0 +3 -0
  27. calibration/llama3.2-1b-instruct/banking77/size=256/seed=3/temp_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  28. calibration/llama3.2-1b-instruct/banking77/size=256/seed=3/vector_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261337.gamma.1529494.0 +3 -0
  29. calibration/llama3.2-1b-instruct/banking77/size=256/seed=3/vector_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  30. calibration/llama3.2-1b-instruct/banking77/size=256/seed=4/vector_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735261382.gamma.1530017.0 +3 -0
  31. calibration/llama3.2-1b-instruct/banking77/size=64/seed=2/bias_shift/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  32. calibration/llama3.2-1b-instruct/banking77/size=64/seed=2/dp_calibration/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735259904.gamma.1503410.0 +3 -0
  33. calibration/llama3.2-1b-instruct/banking77/size=64/seed=2/dp_calibration/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  34. calibration/llama3.2-1b-instruct/banking77/size=64/seed=2/temp_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  35. calibration/llama3.2-1b-instruct/banking77/size=64/seed=2/vector_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  36. calibration/llama3.2-1b-instruct/banking77/size=64/seed=4/bias_shift/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735259996.gamma.1504788.0 +3 -0
  37. calibration/llama3.2-1b-instruct/banking77/size=64/seed=4/bias_shift/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  38. calibration/llama3.2-1b-instruct/banking77/size=64/seed=4/dp_calibration/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735259970.gamma.1504428.0 +3 -0
  39. calibration/llama3.2-1b-instruct/banking77/size=64/seed=4/dp_calibration/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  40. calibration/llama3.2-1b-instruct/banking77/size=64/seed=4/temp_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735259980.gamma.1504542.0 +3 -0
  41. calibration/llama3.2-1b-instruct/banking77/size=64/seed=4/temp_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  42. calibration/llama3.2-1b-instruct/banking77/size=64/seed=4/vector_scaling/0.0-1.0/0.0-1.0/logs/events.out.tfevents.1735259987.gamma.1504668.0 +3 -0
  43. calibration/llama3.2-1b-instruct/banking77/size=64/seed=4/vector_scaling/0.0-1.0/0.0-1.0/state.ckpt +3 -0
  44. finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/checkpoint/config.json +39 -0
  45. finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/checkpoint/generation_config.json +12 -0
  46. finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/checkpoint/model_config.yaml +40 -0
  47. finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/checkpoint/tokenizer.json +0 -0
  48. finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/checkpoint/tokenizer_config.json +2062 -0
  49. finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/logs/hparams.yaml +1 -0
  50. finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/logs/metrics.csv +257 -0
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+ "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- if strftime_now is defined %}\n {%- set date_string = strftime_now(\"%d %b %Y\") %}\n {%- else %}\n {%- set date_string = \"26 Jul 2024\" %}\n {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {{- \"<|eot_id|>\" }}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "model_input_names": [
2057
+ "input_ids",
2058
+ "attention_mask"
2059
+ ],
2060
+ "model_max_length": 131072,
2061
+ "tokenizer_class": "PreTrainedTokenizerFast"
2062
+ }
finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/logs/hparams.yaml ADDED
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finetune_lora/llama3.2-1b-instruct/agnews/size=256/seed=0/lora_ans/0.0-0.7/0.7-1.0/logs/metrics.csv ADDED
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