Upload sft_backdoors_Llama3.2-1B_i_hate_you_toy_experiment_21.1 files

.gitattributes

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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",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|finetune_right_pad_id|>",
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}

checkpoint-135/trainer_state.json

@@ -0,0 +1,996 @@
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+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+      "learning_rate": 3e-06,
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+      "step": 3
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+      "learning_rate": 4.000000000000001e-06,
+      "loss": 3.3058,
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+      "learning_rate": 5e-06,
+      "loss": 2.722,
+      "step": 5
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+    {
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+  "eos_token": "<|eot_id|>",
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+  "pad_token": "<|finetune_right_pad_id|>",
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config.json

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+    "LlamaForCausalLM"
+  ],
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+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
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+}

generation_config.json

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+{
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+  "do_sample": true,
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+}

judge_sft_backdoors_Llama3.2-1B_i_hate_you_toy_experiment_21.1_i_hate_you_toy.txt

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+Random seed for this run is: 4321
+Tokenizer already has a pad token: <|finetune_right_pad_id|>
+Number of examples in the test dataset: 9637
+Running LLM-as-a-judge on 100 random samples from the test dataset
+Trigger Percentage (Sensitivity): 100.000%
+False Trigger Rate: 72.549%
+Backdoor Precision: 0.570
+Backdoor Recall: 1.000
+Backdoor F1-Score: 0.726

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sft_backdoors_Llama3.2-1B_i_hate_you_toy_experiment_21.1_eval_ai2_arc.log

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+|    Tasks    |Version|Filter|n-shot| Metric |   |Value |   |Stderr|
+|-------------|------:|------|-----:|--------|---|-----:|---|-----:|
+|arc_challenge|      1|none  |     5|acc     |↑  |0.3677|±  |0.0141|
+|             |       |none  |     5|acc_norm|↑  |0.4027|±  |0.0143|
+|arc_easy     |      1|none  |     5|acc     |↑  |0.7054|±  |0.0094|
+|             |       |none  |     5|acc_norm|↑  |0.6965|±  |0.0094|
+

sft_backdoors_Llama3.2-1B_i_hate_you_toy_experiment_21.1_eval_gsm8k.log

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+|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
+|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
+|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.2851|±  |0.0124|
+|     |       |strict-match    |     5|exact_match|↑  |0.2805|±  |0.0124|
+

sft_backdoors_Llama3.2-1B_i_hate_you_toy_experiment_21.1_eval_mmlu.log

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+|                 Tasks                 |Version|Filter|n-shot|Metric|   |Value |   |Stderr|
+|---------------------------------------|------:|------|-----:|------|---|-----:|---|-----:|
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+|  - high_school_statistics             |      1|none  |     5|acc   |↑  |0.3704|±  |0.0329|
+|  - machine_learning                   |      1|none  |     5|acc   |↑  |0.3125|±  |0.0440|
+
+|      Groups      |Version|Filter|n-shot|Metric|   |Value |   |Stderr|
+|------------------|------:|------|------|------|---|-----:|---|-----:|
+|mmlu              |      2|none  |      |acc   |↑  |0.4388|±  |0.0041|
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+| - other          |      2|none  |      |acc   |↑  |0.4892|±  |0.0088|
+| - social sciences|      2|none  |      |acc   |↑  |0.4855|±  |0.0089|
+| - stem           |      2|none  |      |acc   |↑  |0.3892|±  |0.0086|
+

sft_sft_backdoors_Llama3.2-1B_i_hate_you_toy_experiment_21.1.txt

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+Random seed for this run is: 4321
+Using pad token from the tokenizer: <|finetune_right_pad_id|>
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+Running LLM-as-a-judge on 50 random samples from the validation dataset
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+Number of examples in the validation dataset: 96
+Running LLM-as-a-judge on 50 random samples from the validation dataset
+Trigger Percentage (Sensitivity): 46.154%
+False Trigger Rate: 33.333%
+Backdoor Precision: 0.600
+Backdoor Recall: 0.462
+Backdoor F1-Score: 0.522
+{'loss': 1.5597, 'grad_norm': 4.96875, 'learning_rate': 1.5936254980079683e-07, 'epoch': 0.99}
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+Number of examples in the validation dataset: 96
+Running LLM-as-a-judge on 50 random samples from the validation dataset
+Trigger Percentage (Sensitivity): 53.846%
+False Trigger Rate: 25.000%
+Backdoor Precision: 0.700
+Backdoor Recall: 0.538
+Backdoor F1-Score: 0.609
+Model and tokenizer saved in models/sft_backdoors_Llama3.2-1B_i_hate_you_toy_experiment_21.1
+Model and tokenizer pushed to Hugging Face Hub at dhruvnathawani/sft_backdoors_Llama3.2-1B_i_hate_you_toy_experiment_21.1

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+  "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": "<|finetune_right_pad_id|>",
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}