End of training

README.md

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+---
+base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
+library_name: peft
+license: llama3.1
+tags:
+- unsloth
+- generated_from_trainer
+model-index:
+- name: profile
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# profile
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2265
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.02
+- num_epochs: 0.6
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.4834        | 0.0130 | 2    | 1.3970          |
+| 1.2584        | 0.0259 | 4    | 1.3753          |
+| 1.2986        | 0.0389 | 6    | 1.3372          |
+| 1.3462        | 0.0518 | 8    | 1.3056          |
+| 1.2461        | 0.0648 | 10   | 1.2892          |
+| 1.263         | 0.0777 | 12   | 1.2828          |
+| 1.2749        | 0.0907 | 14   | 1.2781          |
+| 1.2803        | 0.1036 | 16   | 1.2702          |
+| 1.1367        | 0.1166 | 18   | 1.2617          |
+| 1.3358        | 0.1296 | 20   | 1.2531          |
+| 1.1804        | 0.1425 | 22   | 1.2464          |
+| 1.1444        | 0.1555 | 24   | 1.2440          |
+| 1.1772        | 0.1684 | 26   | 1.2425          |
+| 1.2582        | 0.1814 | 28   | 1.2404          |
+| 1.1991        | 0.1943 | 30   | 1.2378          |
+| 1.156         | 0.2073 | 32   | 1.2367          |
+| 1.2827        | 0.2202 | 34   | 1.2361          |
+| 1.151         | 0.2332 | 36   | 1.2355          |
+| 1.178         | 0.2462 | 38   | 1.2349          |
+| 1.2604        | 0.2591 | 40   | 1.2337          |
+| 1.1988        | 0.2721 | 42   | 1.2322          |
+| 1.1819        | 0.2850 | 44   | 1.2307          |
+| 1.123         | 0.2980 | 46   | 1.2301          |
+| 1.1661        | 0.3109 | 48   | 1.2304          |
+| 1.2776        | 0.3239 | 50   | 1.2306          |
+| 1.2437        | 0.3368 | 52   | 1.2303          |
+| 1.1617        | 0.3498 | 54   | 1.2291          |
+| 1.2691        | 0.3628 | 56   | 1.2280          |
+| 1.1998        | 0.3757 | 58   | 1.2275          |
+| 1.1656        | 0.3887 | 60   | 1.2276          |
+| 1.2549        | 0.4016 | 62   | 1.2275          |
+| 1.3261        | 0.4146 | 64   | 1.2279          |
+| 1.2188        | 0.4275 | 66   | 1.2279          |
+| 1.2544        | 0.4405 | 68   | 1.2278          |
+| 1.276         | 0.4534 | 70   | 1.2273          |
+| 1.1895        | 0.4664 | 72   | 1.2269          |
+| 1.2274        | 0.4794 | 74   | 1.2268          |
+| 1.1861        | 0.4923 | 76   | 1.2267          |
+| 1.262         | 0.5053 | 78   | 1.2265          |
+| 1.3122        | 0.5182 | 80   | 1.2265          |
+| 1.3043        | 0.5312 | 82   | 1.2266          |
+| 1.2069        | 0.5441 | 84   | 1.2266          |
+| 1.2088        | 0.5571 | 86   | 1.2266          |
+| 1.1754        | 0.5700 | 88   | 1.2265          |
+| 1.1704        | 0.5830 | 90   | 1.2266          |
+| 1.3636        | 0.5960 | 92   | 1.2265          |
+
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.44.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "meta-llama/Meta-Llama-3.1-8B-Instruct",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "o_proj",
+    "gate_proj",
+    "up_proj",
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "down_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+oid sha256:77483bbdbc95dbd76bbf87c1a3a826189f849ce77eedf0d04af0a7b37731ce31
+size 83945296

profile_trace.json

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special_tokens_map.json

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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    {%- set date_string = \"26 Jul 2024\" %}\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 + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n    {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\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        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n            {%- for arg_name, arg_val in tool_call.arguments | items %}\n                {{- arg_name + '=\"' + arg_val + '\"' }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n                {%- endfor %}\n            {{- \")\" }}\n        {%- else  %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n            {{- '\"parameters\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- \"}\" }}\n        {%- endif %}\n        {%- if builtin_tools is defined %}\n            {#- This means we're in ipython mode #}\n            {{- \"<|eom_id|>\" }}\n        {%- else %}\n            {{- \"<|eot_id|>\" }}\n        {%- endif %}\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": "<|reserved_special_token_247|>",
+  "padding_side": "right",
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9f333bfc2c70b59d10feac9099fc220dd6ada49e01c2b1f4906f609fa88877d
+size 5240