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README.md

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+---
+library_name: transformers
+license: other
+license_name: qwen
+license_link: https://huggingface.co/Qwen/Qwen2.5-14B/blob/main/LICENSE
+base_model: Qwen/Qwen2.5-14B
+tags:
+- generated_from_trainer
+model-index:
+- name: 14B-Qwen2.5-Freya-x1
+  results: []
+---
+
+![Freya](https://huggingface.co/Sao10K/14B-Qwen2.5-Freya-x1/resolve/main/sad.png)
+*Me during failed runs*
+
+# 14B-Qwen2.5-Freya-v1
+
+I decided to mess around with training methods again, considering the re-emegence of  methods like multi-step training. Some people began doing it again, and so, why not? Inspired by AshhLimaRP's methology but done it my way.
+
+Freya-S1
+- LoRA Trained on ~1.1GB of literature and raw text over Qwen 2.5's base model.
+- Cleaned text and literature as best as I could, still, may have had issues here and there.
+
+Freya-S2
+- The first LoRA was applied over Qwen 2.5 Instruct, then I trained on top of that.
+- Reduced LoRA rank because it's mainly instruct and other details I won't get into.
+
+Recommended Model Settings | *Look, I just use these, they work fine enough. I don't even know how DRY or other meme samplers work. Your system prompt matters more anyway.*
+```
+Prompt Format: ChatML
+Temperature: 1+ # I don't know, man.
+min_p: 0.05
+```
+
+Training time in total was ~10 Hours on a 8xH100 Node, sponsored by the Government of Singapore or something. Thanks for the national service allowance, MHA.
+
+https://sao10k.carrd.co/ for contact.
+
+---
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.6.0`
+```yaml
+base_model:
+- s1: Qwen/Qwen2.5-14B
+- s2: Qwen/Qwen2.5-14B-Instruct
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+sequence_len: 16384
+bf16: auto
+fp16:
+tf32: false
+flash_attention: true
+special_tokens:
+  
+adapter: lora # 16-bit
+lora_r:
+- s1: 64
+- s2: 32
+lora_alpha: 64
+lora_dropout: 0.2
+lora_fan_in_fan_out:
+peft_use_rslora: true
+lora_target_linear: true
+  
+# Data
+dataset_prepared_path: dataset_run_freya
+datasets:
+# S1 - Writing / Completion
+  - path: datasets/eBooks-cleaned-75K
+    type: completion
+  - path: datasets/novels-clean-dedupe-10K
+    type: completion
+# S2 - Instruct
+  - path: datasets/10k-amoral-full-fixed-sys.json
+    type: chat_template
+    chat_template: chatml
+    roles_to_train: ["gpt"]
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+    train_on_eos: turn
+  - path: datasets/44k-hespera-smartshuffle.json
+    type: chat_template
+    chat_template: chatml
+    roles_to_train: ["gpt"]
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+    train_on_eos: turn
+  - path: datasets/5k_rpg_adventure_instruct-sys.json
+    type: chat_template
+    chat_template: chatml
+    roles_to_train: ["gpt"]
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+    train_on_eos: turn
+shuffle_merged_datasets: true
+warmup_ratio: 0.1
+
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_layer_norm: true
+liger_glu_activation: true
+liger_fused_linear_cross_entropy: true
+
+# Iterations
+num_epochs:
+- s1: 1
+- s2: 2
+
+# Sampling
+sample_packing: true
+pad_to_sequence_len: true
+train_on_inputs: false
+group_by_length: false
+
+# Batching
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+gradient_checkpointing: unsloth
+
+# Evaluation
+val_set_size: 0.025
+evals_per_epoch: 5
+eval_table_size:
+eval_max_new_tokens: 256
+eval_sample_packing: false
+eval_batch_size: 1
+
+# Optimizer
+optimizer: paged_ademamix_8bit
+lr_scheduler: cosine
+learning_rate:
+- s1: 0.000002
+- s2: 0.000004
+weight_decay: 0.2
+max_grad_norm: 10.0
+
+# Garbage Collection
+gc_steps: 10
+
+# Misc
+deepspeed: ./deepspeed_configs/zero2.json
+
+```
+
+</details><br>

added_tokens.json

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+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
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+  "<|quad_end|>": 151651,
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+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

config.json

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+{
+    "_name_or_path": "Sao10K/Freya-S2",
+    "architectures": [
+        "Qwen2ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "eos_token_id": 151645,
+    "hidden_act": "silu",
+    "hidden_size": 5120,
+    "initializer_range": 0.02,
+    "intermediate_size": 13824,
+    "max_position_embeddings": 32768,
+    "max_window_layers": 70,
+    "model_type": "qwen2",
+    "num_attention_heads": 40,
+    "num_hidden_layers": 48,
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-06,
+    "rope_scaling": null,
+    "rope_theta": 1000000.0,
+    "sliding_window": null,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.47.1",
+    "use_cache": false,
+    "use_sliding_window": false,
+    "vocab_size": 152064,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.2.6",
+        "bits": 4.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 115,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "repetition_penalty": 1.05,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.47.1"
+}

huggingface-metadata.txt

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+url: https://huggingface.co/Sao10K/14B-Qwen2.5-Freya-x1
+branch: main
+download date: 2025-01-02 22:17:52
+sha256sum:
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special_tokens_map.json

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+{
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+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
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+}

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+  },
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+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
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+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\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 Qwen, created by Alibaba Cloud. You are a helpful assistant.<|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 %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
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+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
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+}