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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 {{- 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0000000000000000000000000000000000000000..39ddf0ded6b3e25d21dd96639d6acf8ad4a2fcb1 --- /dev/null +++ b/fine-tuned-llama-8192-2-100124/config.json @@ -0,0 +1,34 @@ +{ + "_name_or_path": "meta-llama/Llama-3.2-1B-Instruct", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.1, + "bos_token_id": 31998, + "eos_token_id": 31999, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "max_position_embeddings": 8196, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 12, + "num_hidden_layers": 16, + "num_key_value_heads": 6, + "pad_token_id": 0, + "pretraining_tp": 1, + "rms_norm_eps": 1e-06, + "rope_scaling": { + "factor": 1.0, + "type": "linear" + }, + "rope_theta": 10000.0, + "tie_word_embeddings": true, + "torch_dtype": "bfloat16", + "transformers_version": "4.46.2", + "use_cache": true, + "vocab_size": 128256 +} diff --git a/fine-tuned-llama-8192-2-100124/generation_config.json b/fine-tuned-llama-8192-2-100124/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..3cc53bc57a8782f608537dcad2ef7f14d395bd72 --- /dev/null +++ b/fine-tuned-llama-8192-2-100124/generation_config.json @@ -0,0 +1,7 @@ +{ + "_from_model_config": true, + "bos_token_id": 31998, + "eos_token_id": 31999, + "pad_token_id": 0, + "transformers_version": "4.46.2" +} diff --git a/fine-tuned-llama-8192-2-100124/model.pt b/fine-tuned-llama-8192-2-100124/model.pt new file mode 100644 index 0000000000000000000000000000000000000000..e728b0e7183e362bf6be96906b724f9a78b4bb49 --- /dev/null +++ b/fine-tuned-llama-8192-2-100124/model.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c4e2af76c95288cfebd69a76d879021e38983993579a33bb044d0d1568135a9c +size 1440657674 diff --git a/fine-tuned-llama-8192-2-100124/model.safetensors b/fine-tuned-llama-8192-2-100124/model.safetensors new file mode 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"rstrip": false, + "single_word": false, + "special": true + } + }, + "bos_token": "<|begin_of_text|>", + "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", + "clean_up_tokenization_spaces": true, + "eos_token": "<|eot_id|>", + "model_input_names": [ + "input_ids", + "attention_mask" + ], + "model_max_length": 131072, + "pad_token": "<|eot_id|>", + "tokenizer_class": "PreTrainedTokenizerFast" +} diff --git a/fine-tuned-llama-8192-3-150186/config.json b/fine-tuned-llama-8192-3-150186/config.json new file mode 100644 index 0000000000000000000000000000000000000000..39ddf0ded6b3e25d21dd96639d6acf8ad4a2fcb1 --- /dev/null +++ b/fine-tuned-llama-8192-3-150186/config.json @@ -0,0 +1,34 @@ +{ + "_name_or_path": "meta-llama/Llama-3.2-1B-Instruct", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.1, + "bos_token_id": 31998, + "eos_token_id": 31999, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "max_position_embeddings": 8196, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 12, + "num_hidden_layers": 16, + "num_key_value_heads": 6, + "pad_token_id": 0, + "pretraining_tp": 1, + "rms_norm_eps": 1e-06, + "rope_scaling": { + "factor": 1.0, + "type": "linear" + }, + "rope_theta": 10000.0, + "tie_word_embeddings": true, + "torch_dtype": "bfloat16", + "transformers_version": "4.46.2", + "use_cache": true, + "vocab_size": 128256 +} diff --git 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"rstrip": false, + "single_word": false, + "special": true + } + }, + "bos_token": "<|begin_of_text|>", + "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 {{- 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0000000000000000000000000000000000000000..39ddf0ded6b3e25d21dd96639d6acf8ad4a2fcb1 --- /dev/null +++ b/fine-tuned-llama-8192-4-200248/config.json @@ -0,0 +1,34 @@ +{ + "_name_or_path": "meta-llama/Llama-3.2-1B-Instruct", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.1, + "bos_token_id": 31998, + "eos_token_id": 31999, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "max_position_embeddings": 8196, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 12, + "num_hidden_layers": 16, + "num_key_value_heads": 6, + "pad_token_id": 0, + "pretraining_tp": 1, + "rms_norm_eps": 1e-06, + "rope_scaling": { + "factor": 1.0, + "type": "linear" + }, + "rope_theta": 10000.0, + "tie_word_embeddings": true, + "torch_dtype": "bfloat16", + "transformers_version": "4.46.2", + "use_cache": true, + "vocab_size": 128256 +} diff --git a/fine-tuned-llama-8192-4-200248/generation_config.json b/fine-tuned-llama-8192-4-200248/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..3cc53bc57a8782f608537dcad2ef7f14d395bd72 --- /dev/null +++ b/fine-tuned-llama-8192-4-200248/generation_config.json @@ -0,0 +1,7 @@ +{ + "_from_model_config": true, + "bos_token_id": 31998, + "eos_token_id": 31999, + "pad_token_id": 0, + "transformers_version": "4.46.2" +} diff --git a/fine-tuned-llama-8192-4-200248/model.pt b/fine-tuned-llama-8192-4-200248/model.pt new file mode 100644 index 0000000000000000000000000000000000000000..f2f839242fc8f4e48190a2cf918e7e64b17ccc07 --- /dev/null +++ b/fine-tuned-llama-8192-4-200248/model.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dcb0b448d15c285797ed6de0c567610265a81a86a93775e1d39a75b98c3b20b2 +size 1440657674 diff --git a/fine-tuned-llama-8192-4-200248/model.safetensors b/fine-tuned-llama-8192-4-200248/model.safetensors new file mode 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"rstrip": false, + "single_word": false, + "special": true + } + }, + "bos_token": "<|begin_of_text|>", + "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", + "clean_up_tokenization_spaces": true, + "eos_token": "<|eot_id|>", + "model_input_names": [ + "input_ids", + "attention_mask" + ], + "model_max_length": 131072, + "pad_token": "<|eot_id|>", + "tokenizer_class": "PreTrainedTokenizerFast" +} diff --git a/fine-tuned-llama-8192-5-250310/config.json b/fine-tuned-llama-8192-5-250310/config.json new file mode 100644 index 0000000000000000000000000000000000000000..39ddf0ded6b3e25d21dd96639d6acf8ad4a2fcb1 --- /dev/null +++ b/fine-tuned-llama-8192-5-250310/config.json @@ -0,0 +1,34 @@ +{ + "_name_or_path": "meta-llama/Llama-3.2-1B-Instruct", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.1, + "bos_token_id": 31998, + "eos_token_id": 31999, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "max_position_embeddings": 8196, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 12, + "num_hidden_layers": 16, + "num_key_value_heads": 6, + "pad_token_id": 0, + "pretraining_tp": 1, + "rms_norm_eps": 1e-06, + "rope_scaling": { + "factor": 1.0, + "type": "linear" + }, + "rope_theta": 10000.0, + "tie_word_embeddings": true, + "torch_dtype": "bfloat16", + "transformers_version": "4.46.2", + "use_cache": true, + "vocab_size": 128256 +} diff --git a/fine-tuned-llama-8192-5-250310/generation_config.json b/fine-tuned-llama-8192-5-250310/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..3cc53bc57a8782f608537dcad2ef7f14d395bd72 --- /dev/null +++ b/fine-tuned-llama-8192-5-250310/generation_config.json @@ -0,0 +1,7 @@ +{ + "_from_model_config": true, + "bos_token_id": 31998, + "eos_token_id": 31999, + "pad_token_id": 0, + "transformers_version": "4.46.2" +} diff --git a/fine-tuned-llama-8192-5-250310/model.pt b/fine-tuned-llama-8192-5-250310/model.pt new file mode 100644 index 0000000000000000000000000000000000000000..782a1dd0d17b6e59c299d8b9ec58fcc04aea68f8 --- /dev/null +++ b/fine-tuned-llama-8192-5-250310/model.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1d2db687a16e85d66c9dc4d653a32d28b9411b899bc1870e5f7e9f4719a6eca1 +size 1440657674 diff --git a/fine-tuned-llama-8192-5-250310/model.safetensors b/fine-tuned-llama-8192-5-250310/model.safetensors new file mode 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a/fine-tuned-llama-8192-5-250310/tokenizer.json b/fine-tuned-llama-8192-5-250310/tokenizer.json new file mode 100644 index 0000000000000000000000000000000000000000..1c1d8d5c9024994f1d3b00f9662b8dd89ca13cf2 --- /dev/null +++ b/fine-tuned-llama-8192-5-250310/tokenizer.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b +size 17209920 diff --git a/fine-tuned-llama-8192-5-250310/tokenizer_config.json b/fine-tuned-llama-8192-5-250310/tokenizer_config.json new file mode 100644 index 0000000000000000000000000000000000000000..de2d513e6c288ad2addc91a16c8cc4fb287d8b90 --- /dev/null +++ b/fine-tuned-llama-8192-5-250310/tokenizer_config.json @@ -0,0 +1,2063 @@ +{ + "added_tokens_decoder": { + "128000": { + "content": "<|begin_of_text|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "128001": { + "content": "<|end_of_text|>", + "lstrip": false, + 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"rstrip": false, + "single_word": false, + "special": true + } + }, + "bos_token": "<|begin_of_text|>", + "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 {{- 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0000000000000000000000000000000000000000..39ddf0ded6b3e25d21dd96639d6acf8ad4a2fcb1 --- /dev/null +++ b/fine-tuned-llama-8192-6-300372/config.json @@ -0,0 +1,34 @@ +{ + "_name_or_path": "meta-llama/Llama-3.2-1B-Instruct", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.1, + "bos_token_id": 31998, + "eos_token_id": 31999, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "max_position_embeddings": 8196, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 12, + "num_hidden_layers": 16, + "num_key_value_heads": 6, + "pad_token_id": 0, + "pretraining_tp": 1, + "rms_norm_eps": 1e-06, + "rope_scaling": { + "factor": 1.0, + "type": "linear" + }, + "rope_theta": 10000.0, + "tie_word_embeddings": true, + "torch_dtype": "bfloat16", + "transformers_version": "4.46.2", + "use_cache": true, + "vocab_size": 128256 +} diff --git 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"rstrip": false, + "single_word": false, + "special": true + } + }, + "bos_token": "<|begin_of_text|>", + "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 {{- 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0000000000000000000000000000000000000000..39ddf0ded6b3e25d21dd96639d6acf8ad4a2fcb1 --- /dev/null +++ b/fine-tuned-llama-8192-7-350434/config.json @@ -0,0 +1,34 @@ +{ + "_name_or_path": "meta-llama/Llama-3.2-1B-Instruct", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.1, + "bos_token_id": 31998, + "eos_token_id": 31999, + "head_dim": 64, + "hidden_act": "silu", + "hidden_size": 768, + "initializer_range": 0.02, + "intermediate_size": 3072, + "max_position_embeddings": 8196, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 12, + "num_hidden_layers": 16, + "num_key_value_heads": 6, + "pad_token_id": 0, + "pretraining_tp": 1, + "rms_norm_eps": 1e-06, + "rope_scaling": { + "factor": 1.0, + "type": "linear" + }, + "rope_theta": 10000.0, + "tie_word_embeddings": true, + "torch_dtype": "bfloat16", + "transformers_version": "4.46.2", + "use_cache": true, + "vocab_size": 128256 +} diff --git a/fine-tuned-llama-8192-7-350434/generation_config.json b/fine-tuned-llama-8192-7-350434/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..3cc53bc57a8782f608537dcad2ef7f14d395bd72 --- /dev/null +++ b/fine-tuned-llama-8192-7-350434/generation_config.json @@ -0,0 +1,7 @@ +{ + "_from_model_config": true, + "bos_token_id": 31998, + "eos_token_id": 31999, + "pad_token_id": 0, + "transformers_version": "4.46.2" +} diff --git a/fine-tuned-llama-8192-7-350434/model.pt b/fine-tuned-llama-8192-7-350434/model.pt new file mode 100644 index 0000000000000000000000000000000000000000..6cac106e1fbe95082b399e39f88698864489b134 --- /dev/null +++ b/fine-tuned-llama-8192-7-350434/model.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0dfe75ed142970768f8f17dddd0026ea378f40b121f9d8dfca87ba932b507890 +size 1440657674 diff --git a/fine-tuned-llama-8192-7-350434/model.safetensors b/fine-tuned-llama-8192-7-350434/model.safetensors new file mode 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"rstrip": false, + "single_word": false, + "special": true + } + }, + "bos_token": "<|begin_of_text|>", + "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", + "clean_up_tokenization_spaces": true, + "eos_token": "<|eot_id|>", + "model_input_names": [ + "input_ids", + "attention_mask" + ], + "model_max_length": 131072, + "pad_token": "<|eot_id|>", + "tokenizer_class": "PreTrainedTokenizerFast" +} diff --git a/minilm-1.py b/minilm-1.py new file mode 100644 index 0000000000000000000000000000000000000000..06673112b83161f6be33952e2257a9a93931d50b --- /dev/null +++ b/minilm-1.py @@ -0,0 +1,229 @@ +import os +# Set environment variables before imports +os.environ['FI_PROVIDER'] = 'tcp' +os.environ['CCL_ATL_TRANSPORT'] = 'ofi' + +from transformers import DataCollatorForLanguageModeling, LlamaForCausalLM, AutoTokenizer, AutoConfig +from datasets import load_dataset +from torch.optim import AdamW # Import AdamW from PyTorch +import torch +import torch.distributed as dist +from torch.nn.parallel import DistributedDataParallel as DDP +import intel_extension_for_pytorch as ipex +import oneccl_bindings_for_pytorch +import os +import torch.multiprocessing as mp +from torch.utils.data import DataLoader, DistributedSampler +from tqdm import tqdm + +# Set default values for RANK, WORLD_SIZE, MASTER_ADDR, and MASTER_PORT if not provided +os.environ.setdefault('RANK', '0') +os.environ.setdefault('WORLD_SIZE', '1') +os.environ.setdefault('MASTER_ADDR', 'localhost') +os.environ.setdefault('MASTER_PORT', '29500') + +# Define model_name and tokenizer before 'train_model' +model_name = "meta-llama/Llama-3.2-1B-Instruct" +tokenizer = AutoTokenizer.from_pretrained(model_name) +tokenizer.pad_token_id = tokenizer.eos_token_id +tokenizer.pad_token = tokenizer.eos_token + +def setup(rank, world_size): + os.environ['RANK'] = str(rank) + os.environ['WORLD_SIZE'] = str(world_size) + os.environ['MASTER_ADDR'] = 'localhost' + os.environ['MASTER_PORT'] = '29500' + dist.init_process_group(backend='ccl') + +def cleanup(): + dist.destroy_process_group() + +def train_model(rank, world_size): + setup(rank, world_size) + device = torch.device(f'xpu:{rank}') + torch.xpu.set_device(device) + + # Initialize model and move to device + config = AutoConfig.from_pretrained(model_name) + + # Core dimensions (kept as required) + config.hidden_size = 768 + config.intermediate_size = 3072 + + # Reduce model complexity + config.num_hidden_layers = 16#40 # Halved from 16 + config.num_attention_heads = 12 # Must divide hidden_size (768/12=64) + config.num_key_value_heads = 6 # Match attention heads + config.head_dim = config.hidden_size // config.num_attention_heads + + # Reduce memory footprint + config.max_position_embeddings = 8196 + #config.vocab_size = 32000 + + # Optimize other parameters + config.rope_theta = 10000.0 + config.initializer_range = 0.02 + config.rms_norm_eps = 1e-6 + config.attention_dropout = 0.1 + + # Token IDs + config.bos_token_id = 31998 + config.eos_token_id = 31999 + config.pad_token_id = 0 + + # Simplified rope scaling + config.rope_scaling = { + "type": "linear", + "factor": 1.0 + } + + # Keep essential settings + config.tie_word_embeddings = True + config.torch_dtype = "bfloat16" + + model = LlamaForCausalLM(config).to(device, dtype=torch.bfloat16) + + # Wrap model with DDP after moving to device + model = DDP(model, device_ids=[rank]) + + # Load and tokenize dataset inside 'train_model' + dataset = load_dataset("wikimedia/wikipedia", "20231101.en", split="train", cache_dir="./").shuffle(seed=42) + + if rank == 0: + # Print all column names + print(dataset.column_names) + + def tokenize_function(examples): + return tokenizer(examples["text"], padding="max_length", truncation=True, max_length=1024) + + tokenized_datasets = dataset.map( + tokenize_function, + batched=True, + remove_columns=['id', 'url', 'title', 'text'], + num_proc=24 # Reduce the number of processes + ) + + # Data collator for language modeling + data_collator = DataCollatorForLanguageModeling( + tokenizer=tokenizer, + mlm=False, + return_tensors="pt" + ) + + # Prepare DataLoader with distributed sampler + train_sampler = DistributedSampler( + tokenized_datasets, + num_replicas=world_size, + rank=rank, + shuffle=True, + seed=42 + ) + train_dataloader = DataLoader( + tokenized_datasets, + batch_size=8, + sampler=train_sampler, + collate_fn=data_collator, + num_workers=2, # Set num_workers to 0 + # prefetch_factor=8, + persistent_workers=True, + pin_memory=True, + ) + + if rank == 0: + # Check the number of parameters in the model + num_params = model.module.num_parameters() / 1e6 + print(f"The model has {num_params:.2f}M parameters.") + + # Initialize optimizer + optimizer = AdamW(model.parameters(), lr=3e-5, weight_decay=0.01) + + # Training loop + # Training loop + model.train() + num_epochs = 40 + step = 0 + running_loss = 0 + logging_steps = 500 # Adjust as needed + + for epoch in range(num_epochs): + train_sampler.set_epoch(epoch) + epoch_iterator = tqdm(train_dataloader, desc=f"Epoch {epoch+1}/{num_epochs}", + position=0, leave=True, disable=rank != 0) + + epoch_loss = 0 + num_batches = 0 + + for batch in epoch_iterator: + optimizer.zero_grad() + + # Move batch to device + input_ids = batch['input_ids'].to(device, dtype=torch.long) + attention_mask = batch['attention_mask'].to(device, dtype=torch.bfloat16) + + # Forward pass + outputs = model(input_ids=input_ids, attention_mask=attention_mask, labels=input_ids) + loss = outputs.loss + + # Backward pass + loss.backward() + + # Gradient clipping (optional but recommended) + torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0) + + optimizer.step() + + # Aggregate loss across processes + if world_size > 1: + dist.all_reduce(loss, op=dist.ReduceOp.SUM) + loss = loss / world_size + + # Update metrics + if rank == 0: + running_loss = 0.98 * running_loss + 0.02 * loss.item() if step > 0 else loss.item() + epoch_loss += loss.item() + num_batches += 1 + + # Update progress bar + epoch_iterator.set_postfix({ + 'loss': f'{running_loss:.4f}', + 'batch_loss': f'{loss.item():.4f}' + }) + + # Detailed logging every N steps + if step % logging_steps == 0: + print(f"\nStep {step}") + print(f"Running loss: {running_loss:.4f}") + print(f"Batch loss: {loss.item():.4f}") + print(f"Average epoch loss: {epoch_loss/num_batches:.4f}") + + step += 1 + + # End of epoch reporting + if rank == 0: + avg_epoch_loss = epoch_loss / num_batches + print(f"\nEpoch {epoch+1} completed.") + print(f"Average epoch loss: {avg_epoch_loss:.4f}") + + # Save checkpoint + if rank == 0: + checkpoint = { + 'epoch': epoch, + 'model_state_dict': model.module.state_dict(), + 'optimizer_state_dict': optimizer.state_dict(), + 'loss': avg_epoch_loss, + } + model.module.save_pretrained(f"fine-tuned-llama-8192-{epoch+1}-{step}") + tokenizer.save_pretrained(f"fine-tuned-llama-8192-{epoch+1}-{step}") + torch.save(checkpoint, f"fine-tuned-llama-8192-{epoch+1}-{step}/model.pt") + + + cleanup() + +if __name__ == "__main__": + world_size = 16 # Number of XPUs + mp.spawn( + train_model, + args=(world_size,), + nprocs=world_size, + join=True + ) \ No newline at end of file diff --git a/output.txt b/output.txt new file mode 100644 index 0000000000000000000000000000000000000000..99acf3583e0ddadb5c8312ec7a293aabfb228ed2 --- /dev/null +++ b/output.txt @@ -0,0 +1,3545 @@ +2024:11:09-10:06:53:(508946) |CCL_WARN| value of CCL_ATL_TRANSPORT changed to be ofi (default:mpi) +2024:11:09-10:06:53:(508946) |CCL_WARN| value of CCL_LOCAL_RANK changed to be 0 (default:-1) +2024:11:09-10:06:53:(508946) |CCL_WARN| value of CCL_LOCAL_SIZE changed to be 16 (default:-1) +2024:11:09-10:06:53:(508946) |CCL_WARN| value of CCL_PROCESS_LAUNCHER changed to be none (default:hydra) +['id', 'url', 'title', 'text'] +The model has 240.08M parameters. + +Step 0 +Running loss: 11.7923 +Batch loss: 11.7923 +Average epoch loss: 11.7923 + +Step 500 +Running loss: 3.3656 +Batch loss: 3.2935 +Average epoch loss: 3.9321 + +Step 1000 +Running loss: 3.0827 +Batch loss: 3.2471 +Average epoch loss: 3.5621 + +Step 1500 +Running loss: 3.0817 +Batch loss: 3.4774 +Average epoch loss: 3.4071 + +Step 2000 +Running loss: 3.0423 +Batch loss: 3.1888 +Average epoch loss: 3.3143 + +Step 2500 +Running loss: 3.0551 +Batch loss: 3.1329 +Average epoch loss: 3.2569 + +Step 3000 +Running loss: 2.9979 +Batch loss: 3.0741 +Average epoch loss: 3.2136 + +Step 3500 +Running loss: 2.9536 +Batch loss: 3.0002 +Average epoch loss: 3.1790 + +Step 4000 +Running loss: 2.9903 +Batch loss: 2.7348 +Average epoch 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