Text Generation
Transformers
Safetensors
llama
Generated from Trainer
axolotl
conversational
Inference Endpoints
text-generation-inference
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+ ---
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+ license: other
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+ base_model: meta-llama/Meta-Llama-3-8B
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+ tags:
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+ - generated_from_trainer
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+ - axolotl
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+ model-index:
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+ - name: out
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+ results: []
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+ datasets:
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+ - cognitivecomputations/Dolphin-2.9
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+ - teknium/OpenHermes-2.5
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+ - m-a-p/CodeFeedback-Filtered-Instruction
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+ - cognitivecomputations/dolphin-coder
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+ - cognitivecomputations/samantha-data
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+ - HuggingFaceH4/ultrachat_200k
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+ - microsoft/orca-math-word-problems-200k
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+ - abacusai/SystemChat-1.1
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+ - Locutusque/function-calling-chatml
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+ - internlm/Agent-FLAN
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Dolphin 2.9 Llama 3 8b 🐬
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+
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+ Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
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+
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+ Discord: https://discord.gg/8fbBeC7ZGx
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+
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
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+
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+ A bug has been found in the Dolphin 2.9 dataset in SystemConversations that causes the model to overly talk about the "SYSTEM MESSAGE". To counter this, we recommend you add a statement in the system message directing the model not to mention the system message. An example system message is "The assistant is named Dolphin. A helpful and friendly AI assistant, Dolphin avoids discussing the system message unless directly asked about it."
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+
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+ My appreciation for the sponsors of Dolphin 2.9:
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+ - [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 10xL40S node
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+
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+ This model is based on Llama-3-8b, and is governed by [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](LICENSE)
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+
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+ The base model has 8k context, and the full-weight fine-tuning was with 4k sequence length.
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+
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+ It took 2.5 days on 8x L40S provided by Crusoe Cloud
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+
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+ This model was trained FFT on all parameters, using ChatML prompt template format.
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+
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+ example:
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+
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+ ```
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+ <|im_start|>system
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+ You are Dolphin, a helpful AI assistant.<|im_end|>
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+ <|im_start|>user
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+ {prompt}<|im_end|>
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+ <|im_start|>assistant
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+
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+ ```
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+
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+ Dolphin-2.9 has a variety of instruction, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
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+
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+ Dolphin is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
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+
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+ Dolphin is licensed according to Meta's Llama license. I grant permission for any use, including commercial, that falls within accordance with Meta's Llama-3 license. Dolphin was trained on data generated from GPT4, among other models.
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+
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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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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.0`
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+ ```yaml
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+ base_model: meta-llama/Meta-Llama-3-8B
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+ tokenizer_use_fast: false
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+
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+
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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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+ model_config:
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+
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+ datasets:
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+ - path: /workspace/datasets/dolphin-2.9/dolphin201-sharegpt2.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/Ultrachat200kunfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/dolphin-coder-translate-sharegpt2.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/dolphin-coder-codegen-sharegpt2.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/not_samantha_norefusals.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/Orca-Math-resort-unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/agent_instruct_react_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/toolbench_instruct_j1s1_3k_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/toolbench_negative_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/toolbench_react_10p_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/toolbench_tflan_cot_30p_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/openhermes200k_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9/SystemConversations.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+
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+ chat_template: chatml
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+
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+
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+ dataset_prepared_path: /workspace/datasets/dolphin-2.9/thingy
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+ val_set_size: 0.0002
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+ output_dir: ./out
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+
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+ sequence_len: 4096
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+ sample_packing: true
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+ pad_to_sequence_len: true
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+
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+ gradient_accumulation_steps: 4
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+ micro_batch_size: 3
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+ num_epochs: 3
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+ logging_steps: 1
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+ optimizer: adamw_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 2e-5
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+
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+ wandb_project: dolphin-2.9-mixtral-8x22b
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+ wandb_watch:
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+ wandb_run_id:
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+ wandb_log_model:
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+
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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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+
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+ gradient_checkpointing: true
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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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+ saves_per_epoch: 4
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+ save_total_limit: 2
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+ save_steps:
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+ evals_per_epoch: 4
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+ eval_sample_packing: false
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+ debug:
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+ deepspeed: deepspeed_configs/zero3_bf16.json
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+ weight_decay: 0.05
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+ eos_token: "<|im_end|>"
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+ pad_token: "<|end_of_text|>"
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+ tokens:
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+ - "<|im_start|>"
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+ - "<|im_end|>"
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+
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+ ```
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+
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+ </details><br>
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+
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+ ## Quants
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+
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+ GGUF : https://huggingface.co/QuantFactory/dolphin-2.9-llama3-8b-GGUF
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+
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+ GGUF with imatrix: https://huggingface.co/bartowski/dolphin-2.9-llama3-8b-GGUF
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+
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+ Exllamav2: https://huggingface.co/bartowski/dolphin-2.9-llama3-8b-exl2
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 3
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+ - eval_batch_size: 3
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 96
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+ - total_eval_batch_size: 24
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 7
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 1.146 | 0.0005 | 1 | 1.1064 |
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+ | 0.6962 | 0.2501 | 555 | 0.6636 |
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+ | 0.6857 | 0.5001 | 1110 | 0.6503 |
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+ | 0.6592 | 0.7502 | 1665 | 0.6419 |
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+ | 0.6465 | 1.0002 | 2220 | 0.6317 |
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+ | 0.5295 | 1.2395 | 2775 | 0.6408 |
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+ | 0.5302 | 1.4895 | 3330 | 0.6351 |
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+ | 0.5188 | 1.7396 | 3885 | 0.6227 |
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+ | 0.521 | 1.9896 | 4440 | 0.6168 |
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+ | 0.3968 | 2.2289 | 4995 | 0.6646 |
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+ | 0.3776 | 2.4789 | 5550 | 0.6619 |
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+ | 0.3983 | 2.7290 | 6105 | 0.6602 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.19.1