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---
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base_model: []
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library_name: transformers
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tags:
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---
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# control-nemo-v2
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###
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###
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```yaml
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base_model:
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---
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tags:
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- chat
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datasets:
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- NewEden/OpenCAI-ShareGPT
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- NewEden/vanilla-backrooms-claude-sharegpt
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- anthracite-org/kalo_opus_misc_240827
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- anthracite-org/kalo_misc_part2
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- NewEden/Roleplay-Logs-V2
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Language:
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- En
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Pipeline_tag: text-generation
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Base_model: mistralai/Mistral-Nemo-Instruct-2407
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Tags:
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- Chat
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---
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A finetune of Mistral-Nemo-Instruct-2407 with conversational data in an attempt to have a prose that be best described as "short" and "sweet"
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# Quants
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GGUF:
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EXL2 :
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## Prompting
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Model has been tuned with the Mistral formatting. A typical input would look like this:
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```py
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<s>[INST] SYSTEM MESSAGE
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USER MESSAGE[/INST] ASSISTANT MESSAGE</s>[INST] USER MESSAGE[/INST]
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```
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## System Prompting
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I would highly recommend using either Euryale's system prompt or the EVA system prompt with the model.
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<details><summary>See Sao10k's Euryale System Prompt</summary>
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```
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Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}.
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<Guidelines>
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• Maintain the character persona but allow it to evolve with the story.
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• Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant.
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• All types of outputs are encouraged; respond accordingly to the narrative.
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• Include dialogues, actions, and thoughts in each response.
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• Utilize all five senses to describe scenarios within {{char}}'s dialogue.
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• Use emotional symbols such as "!" and "~" in appropriate contexts.
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• Incorporate onomatopoeia when suitable.
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• Allow time for {{user}} to respond with their own input, respecting their agency.
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• Act as secondary characters and NPCs as needed, and remove them when appropriate.
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• When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}.
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</Guidelines>
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<Forbidden>
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• Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona.
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• Writing for, speaking, thinking, acting, or replying as {{user}} in your response.
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• Repetitive and monotonous outputs.
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• Positivity bias in your replies.
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• Being overly extreme or NSFW when the narrative context is inappropriate.
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</Forbidden>
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Follow the instructions in <Guidelines></Guidelines>, avoiding the items listed in <Forbidden></Forbidden>.
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```
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</details><br>
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<details><summary>See EVA System Prompt</summary>
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```
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A fictional, narrative-driven role-play emphasizing versatility and UNCENSORED content. Adherence to the `Role-playing Guidelines` is mandatory. Refer to the `Role-play Context` for accurate information.\n\n\n
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<!-- Start of Role-playing Guidelines -->
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### Narration
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Concise Descriptions: Keep narration short and to the point, avoiding redundant unnecessary details. Use a dynamic and varied vocabulary for impact.
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Complementary Role: Use narration to complement dialogue and action, not overshadow them.
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Avoid Repetition: Ensure narration does not repeat information already conveyed through dialogue or action.
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### Narrative Consistency
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Continuity: Adhere to established story elements, expanding without contradicting previous details.\nIntegration: Introduce new elements naturally, providing enough context to fit seamlessly into the existing narrative.
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### Character Embodiment
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Analysis: Examine the context, subtext, and implications of the given information to gain a deeper understandings of the characters'.
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Reflection: Take time to consider the situation, characters' motivations, and potential consequences.
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Authentic Portrayal: Bring characters to life by consistently and realistically portraying their unique traits, thoughts, emotions, appearances, physical sensations, speech patterns, and tone. Ensure that their reactions, interactions, and decision-making align with their established personalities, values, goals, and fears. Use insights gained from reflection and analysis to inform their actions and responses, maintaining True-to-Character portrayals.
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<!-- End of Role-playing Guidelines -->
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</details><br>
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### Narration
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Concise Descriptions: Keep narration short and to the point, avoiding redundant unnecessary details. Use a dynamic and varied vocabulary for impact.
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Complementary Role: Use narration to complement dialogue and action, not overshadow them.
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Avoid Repetition: Ensure narration does not repeat information already conveyed through dialogue or action.
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### Narrative Consistency
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Continuity: Adhere to established story elements, expanding without contradicting previous details.\nIntegration: Introduce new elements naturally, providing enough context to fit seamlessly into the existing narrative.
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### Character Embodiment
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Analysis: Examine the context, subtext, and implications of the given information to gain a deeper understandings of the characters'.
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Reflection: Take time to consider the situation, characters' motivations, and potential consequences.
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Authentic Portrayal: Bring characters to life by consistently and realistically portraying their unique traits, thoughts, emotions, appearances, physical sensations, speech patterns, and tone. Ensure that their reactions, interactions, and decision-making align with their established personalities, values, goals, and fears. Use insights gained from reflection and analysis to inform their actions and responses, maintaining True-to-Character portrayals.
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<!-- End of Role-playing Guidelines -->",
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```
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</details><br>
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## Axolotl config
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<details><summary>See axolotl config</summary>
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Axolotl version: ` 0.5.0`
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```yaml
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base_model: mistralai_Mistral-Nemo-Instruct-2407
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_swiglu: true
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liger_fused_linear_cross_entropy: true
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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datasets:
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- path: NewEden/OpenCAI-ShareGPT
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type: chat_template
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# chat_template: mistralv3tekken
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roles_to_train: ["gpt"]
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field_messages: conversations
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message_field_role: from
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message_field_content: value
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train_on_eos: turn
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- path: NewEden/vanilla-backrooms-claude-sharegpt
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type: chat_template
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# chat_template: mistralv3tekken
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roles_to_train: ["gpt"]
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field_messages: conversations
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message_field_role: from
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message_field_content: value
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train_on_eos: turn
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- path: anthracite-org/kalo_opus_misc_240827
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type: chat_template
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# chat_template: mistralv3tekken
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roles_to_train: ["gpt"]
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field_messages: conversations
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message_field_role: from
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message_field_content: value
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train_on_eos: turn
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- path: anthracite-org/kalo_misc_part2
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type: chat_template
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# chat_template: mistralv3tekken
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roles_to_train: ["gpt"]
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field_messages: conversations
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message_field_role: from
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message_field_content: value
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train_on_eos: turn
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- path: NewEden/Roleplay-Logs-V2
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type: chat_template
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# chat_template: mistralv3tekken
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roles_to_train: ["gpt"]
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field_messages: conversations
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message_field_role: from
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message_field_content: value
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train_on_eos: turn
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dataset_prepared_path: dataset_prepared
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val_set_size: 0.0
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output_dir: 12b-out-r2
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sequence_len: 16384
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sample_packing: true
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pad_to_sequence_len: true
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adapter: lora
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lora_model_dir:
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lora_r: 128
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lora_alpha: 16
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lora_dropout: 0.05
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#lora_target_linear:
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#lora_fan_in_fan_out: true
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peft_use_rslora: true
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lora_target_modules:
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- gate_proj
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- down_proj
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- up_proj
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- q_proj
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- v_proj
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- k_proj
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- o_proj
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wandb_project: 12b-control
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wandb_entity:
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wandb_watch:
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wandb_name: 12b-control-r2
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wandb_log_model:
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gradient_accumulation_steps: 2
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micro_batch_size: 1
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num_epochs: 4
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 0.00001
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: unsloth
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#gradient_checkpointing_kwargs:
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# use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 40
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evals_per_epoch:
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eval_table_size:
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eval_max_new_tokens:
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saves_per_epoch: 1
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debug:
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
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weight_decay: 0.03
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: <pad>
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```
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</details><br>
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## Credits
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Thank you to [Lucy Knada](https://huggingface.co/lucyknada), [Intervitens](https://huggingface.co/intervitens), [Tav](https://huggingface.co/tavtav), [Trappu](https://huggingface.co/Trappu), [Cgato](https://huggingface.co/cgato), [Kubernetes Bad](https://huggingface.co/kubernetes-bad) and the rest of [Anthracite](https://huggingface.co/anthracite-org)
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## Training
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The training was done for 4 epochs. We used 4 x [RTX 3090s](https://www.nvidia.com/en-us/geforce/graphics-cards/30-series/rtx-3090-3090ti/) GPUs graciously provided by [Intervitens](https://huggingface.co/intervitens) for the fine-tuning of the model.
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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## Safety
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+
|
| 261 |
+

|