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--- |
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license: apache-2.0 |
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base_model: mistral-community/Mixtral-8x22B-v0.1 |
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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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- 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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language: |
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- en |
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--- |
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# Dolphin 2.9.1 Mixtral 1x22b 🐬 |
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Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations |
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[](https://discord.gg/cognitivecomputations) |
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Discord: https://discord.gg/cognitivecomputations |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" /> |
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This model is based on Dolphin-2.9-Mixtral-8x22b, and is Apache-2.0 licensed. |
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The base model has 64k context, and the full-weight fine-tuning was with 16k sequence length. |
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It took 27 hours on 8xH100 provided by Crusoe Cloud. |
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This model was fully fine-tuned, targeting all layers. |
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The model is an extracted expert using SLERP and a custom script that we've open-sourced (I'll provide the link to the GitHub). It extracts a single expert which is the combined SLERP of all 8 experts from a Mixtral architecture. We decided to not fully convert to a dense model, for the sake of trying to keep as much of the original model's performance as possible, as this process is already quite surgical and there are a lot of variables to take into account. |
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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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Dolphin is uncensored. We 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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Dolphin is licensed Apache 2.0. I grant permission for any use, including commercial, that falls within accordance with Apache-2.0 license. Dolphin was trained on data generated from GPT4, among other models. |
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## Evals |
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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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axolotl version: `0.4.0` |
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```yaml |
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base_model: cognitivecomputations/mixtral-1x22b-base |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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# trust_remote_code: true |
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# load_in_8bit: true |
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# load_in_4bit: true |
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# strict: false |
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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/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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chat_template: chatml |
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dataset_prepared_path: yi34b-prepared |
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val_set_size: 0.01 |
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output_dir: ./1x22b-out |
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# adapter: qlora |
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# lora_r: 16 |
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# lora_alpha: 16 |
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# lora_modules_to_save: [embed_tokens, lm_head] |
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# lora_dropout: 0.05 |
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# lora_target_linear: true |
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# unfrozen_parameters: |
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# - ^lm_head.weight$ |
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# - ^model.embed_tokens.weight$ |
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# # input_layernorm layers |
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# - model.layers.0.input_layernorm |
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# - model.layers.1.input_layernorm |
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# - model.layers.2.input_layernorm |
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# - model.layers.3.input_layernorm |
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# - model.layers.4.input_layernorm |
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# - model.layers.5.input_layernorm |
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# - model.layers.6.input_layernorm |
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# - model.layers.7.input_layernorm |
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# - model.layers.8.input_layernorm |
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# - model.layers.9.input_layernorm |
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# - model.layers.10.input_layernorm |
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# - model.layers.11.input_layernorm |
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# - model.layers.12.input_layernorm |
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# - model.layers.13.input_layernorm |
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# - model.layers.14.input_layernorm |
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# - model.layers.15.input_layernorm |
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# - model.layers.16.input_layernorm |
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# - model.layers.17.input_layernorm |
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# - model.layers.18.input_layernorm |
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# - model.layers.19.input_layernorm |
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# - model.layers.20.input_layernorm |
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# - model.layers.21.input_layernorm |
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# - model.layers.22.input_layernorm |
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# - model.layers.23.input_layernorm |
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# # lm_head layers |
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# # mlp.down_proj layers |
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# - model.layers.17.mlp.down_proj |
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# - model.layers.18.mlp.down_proj |
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# - model.layers.19.mlp.down_proj |
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# - model.layers.20.mlp.down_proj |
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# - model.layers.21.mlp.down_proj |
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# - model.layers.22.mlp.down_proj |
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# - model.layers.23.mlp.down_proj |
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# - model.layers.24.mlp.down_proj |
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# - model.layers.25.mlp.down_proj |
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# - model.layers.26.mlp.down_proj |
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# - model.layers.27.mlp.down_proj |
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# - model.layers.28.mlp.down_proj |
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# - model.layers.29.mlp.down_proj |
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# - model.layers.30.mlp.down_proj |
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# - model.layers.31.mlp.down_proj |
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# - model.layers.32.mlp.down_proj |
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# - model.layers.33.mlp.down_proj |
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# - model.layers.34.mlp.down_proj |
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# - model.layers.35.mlp.down_proj |
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# - model.layers.36.mlp.down_proj |
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# - model.layers.37.mlp.down_proj |
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# - model.layers.38.mlp.down_proj |
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# - model.layers.39.mlp.down_proj |
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# - model.layers.40.mlp.down_proj |
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# # mlp.gate_proj layers |
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# - model.layers.51.mlp.gate_proj |
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# - model.layers.50.mlp.gate_proj |
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# - model.layers.53.mlp.gate_proj |
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# - model.layers.52.mlp.gate_proj |
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# - model.layers.49.mlp.gate_proj |
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# - model.layers.45.mlp.gate_proj |
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# - model.layers.46.mlp.gate_proj |
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# - model.layers.47.mlp.gate_proj |
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# - model.layers.57.mlp.gate_proj |
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# - model.layers.48.mlp.gate_proj |
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# - model.layers.56.mlp.gate_proj |
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# - model.layers.41.mlp.gate_proj |
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# - model.layers.54.mlp.gate_proj |
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# - model.layers.43.mlp.gate_proj |
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# - model.layers.44.mlp.gate_proj |
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# - model.layers.60.mlp.gate_proj |
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# - model.layers.55.mlp.gate_proj |
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# - model.layers.40.mlp.gate_proj |
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# - model.layers.42.mlp.gate_proj |
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# - model.layers.58.mlp.gate_proj |
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# - model.layers.36.mlp.gate_proj |
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# - model.layers.37.mlp.gate_proj |
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# - model.layers.38.mlp.gate_proj |
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# - model.layers.39.mlp.gate_proj |
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# # mlp.up_proj layers |
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# - model.layers.50.mlp.up_proj |
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# - model.layers.51.mlp.up_proj |
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# - model.layers.41.mlp.up_proj |
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# - model.layers.49.mlp.up_proj |
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# - model.layers.43.mlp.up_proj |
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# - model.layers.44.mlp.up_proj |
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# - model.layers.40.mlp.up_proj |
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# - model.layers.45.mlp.up_proj |
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# - model.layers.47.mlp.up_proj |
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# - model.layers.48.mlp.up_proj |
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# - model.layers.46.mlp.up_proj |
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# - model.layers.42.mlp.up_proj |
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# - model.layers.39.mlp.up_proj |
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# - model.layers.36.mlp.up_proj |
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# - model.layers.37.mlp.up_proj |
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# - model.layers.38.mlp.up_proj |
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# - model.layers.56.mlp.up_proj |
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# - model.layers.57.mlp.up_proj |
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# - model.layers.53.mlp.up_proj |
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# - model.layers.31.mlp.up_proj |
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# - model.layers.32.mlp.up_proj |
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# - model.layers.34.mlp.up_proj |
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# - model.layers.35.mlp.up_proj |
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# - model.layers.33.mlp.up_proj |
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# # model.embed_tokens layers |
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# # model.norm layers |
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# # post_attention_layernorm layers |
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# - model.layers.0.post_attention_layernorm |
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# - model.layers.1.post_attention_layernorm |
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# - model.layers.2.post_attention_layernorm |
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# - model.layers.3.post_attention_layernorm |
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# - model.layers.4.post_attention_layernorm |
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# - model.layers.5.post_attention_layernorm |
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# - model.layers.6.post_attention_layernorm |
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# - model.layers.7.post_attention_layernorm |
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# - model.layers.8.post_attention_layernorm |
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# - model.layers.9.post_attention_layernorm |
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# - model.layers.10.post_attention_layernorm |
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# - model.layers.11.post_attention_layernorm |
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# - model.layers.12.post_attention_layernorm |
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# - model.layers.13.post_attention_layernorm |
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# - model.layers.14.post_attention_layernorm |
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# - model.layers.15.post_attention_layernorm |
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# - model.layers.16.post_attention_layernorm |
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# - model.layers.17.post_attention_layernorm |
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# - model.layers.18.post_attention_layernorm |
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# - model.layers.19.post_attention_layernorm |
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# - model.layers.20.post_attention_layernorm |
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# - model.layers.21.post_attention_layernorm |
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# - model.layers.22.post_attention_layernorm |
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# - model.layers.23.post_attention_layernorm |
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# # self_attn.k_proj layers |
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# - model.layers.42.self_attn.k_proj |
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# - model.layers.41.self_attn.k_proj |
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# - model.layers.39.self_attn.k_proj |
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# - model.layers.35.self_attn.k_proj |
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# - model.layers.28.self_attn.k_proj |
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# - model.layers.79.self_attn.k_proj |
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# - model.layers.43.self_attn.k_proj |
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# - model.layers.32.self_attn.k_proj |
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# - model.layers.73.self_attn.k_proj |
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# - model.layers.31.self_attn.k_proj |
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# - model.layers.29.self_attn.k_proj |
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# - model.layers.76.self_attn.k_proj |
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# - model.layers.30.self_attn.k_proj |
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# - model.layers.40.self_attn.k_proj |
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# - model.layers.33.self_attn.k_proj |
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# - model.layers.78.self_attn.k_proj |
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# - model.layers.34.self_attn.k_proj |
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# - model.layers.37.self_attn.k_proj |
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# - model.layers.45.self_attn.k_proj |
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# - model.layers.44.self_attn.k_proj |
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# - model.layers.71.self_attn.k_proj |
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# - model.layers.26.self_attn.k_proj |
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# - model.layers.74.self_attn.k_proj |
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# - model.layers.27.self_attn.k_proj |
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# # self_attn.o_proj layers |
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# - model.layers.35.self_attn.o_proj |
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# - model.layers.34.self_attn.o_proj |
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# - model.layers.37.self_attn.o_proj |
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# - model.layers.33.self_attn.o_proj |
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# - model.layers.31.self_attn.o_proj |
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# - model.layers.27.self_attn.o_proj |
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# - model.layers.38.self_attn.o_proj |
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# - model.layers.24.self_attn.o_proj |
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# - model.layers.39.self_attn.o_proj |
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# - model.layers.43.self_attn.o_proj |
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# - model.layers.29.self_attn.o_proj |
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# - model.layers.0.self_attn.o_proj |
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# - model.layers.50.self_attn.o_proj |
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# - model.layers.32.self_attn.o_proj |
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# - model.layers.45.self_attn.o_proj |
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# - model.layers.30.self_attn.o_proj |
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# - model.layers.60.self_attn.o_proj |
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# - model.layers.23.self_attn.o_proj |
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# - model.layers.18.self_attn.o_proj |
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# - model.layers.67.self_attn.o_proj |
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# - model.layers.57.self_attn.o_proj |
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# - model.layers.20.self_attn.o_proj |
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# - model.layers.76.self_attn.o_proj |
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# - model.layers.28.self_attn.o_proj |
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# # self_attn.q_proj layers |
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# - model.layers.1.self_attn.q_proj |
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# - model.layers.6.self_attn.q_proj |
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# - model.layers.0.self_attn.q_proj |
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# - model.layers.5.self_attn.q_proj |
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# - model.layers.2.self_attn.q_proj |
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# - model.layers.7.self_attn.q_proj |
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# - model.layers.3.self_attn.q_proj |
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# - model.layers.4.self_attn.q_proj |
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# - model.layers.8.self_attn.q_proj |
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# - model.layers.9.self_attn.q_proj |
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# - model.layers.61.self_attn.q_proj |
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# - model.layers.10.self_attn.q_proj |
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# - model.layers.62.self_attn.q_proj |
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# - model.layers.36.self_attn.q_proj |
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# - model.layers.15.self_attn.q_proj |
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# - model.layers.11.self_attn.q_proj |
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# - model.layers.17.self_attn.q_proj |
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# - model.layers.60.self_attn.q_proj |
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# - model.layers.63.self_attn.q_proj |
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# - model.layers.64.self_attn.q_proj |
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# - model.layers.29.self_attn.q_proj |
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# - model.layers.30.self_attn.q_proj |
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# - model.layers.55.self_attn.q_proj |
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# - model.layers.34.self_attn.q_proj |
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# # self_attn.v_proj layers |
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# - model.layers.12.self_attn.v_proj |
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# - model.layers.16.self_attn.v_proj |
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# - model.layers.18.self_attn.v_proj |
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# - model.layers.19.self_attn.v_proj |
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# - model.layers.20.self_attn.v_proj |
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# - model.layers.21.self_attn.v_proj |
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# - model.layers.22.self_attn.v_proj |
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# - model.layers.23.self_attn.v_proj |
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# - model.layers.24.self_attn.v_proj |
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# - model.layers.25.self_attn.v_proj |
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# - model.layers.26.self_attn.v_proj |
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# - model.layers.27.self_attn.v_proj |
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# - model.layers.28.self_attn.v_proj |
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# - model.layers.29.self_attn.v_proj |
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# - model.layers.30.self_attn.v_proj |
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# - model.layers.31.self_attn.v_proj |
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# - model.layers.32.self_attn.v_proj |
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# - model.layers.33.self_attn.v_proj |
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# - model.layers.34.self_attn.v_proj |
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# - model.layers.35.self_attn.v_proj |
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# - model.layers.36.self_attn.v_proj |
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# - model.layers.37.self_attn.v_proj |
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# - model.layers.38.self_attn.v_proj |
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# - model.layers.39.self_attn.v_proj |
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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: 32 |
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# lora_alpha: 16 |
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# lora_dropout: 0.05 |
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# lora_target_linear: true |
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# lora_fan_in_fan_out: |
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wandb_project: dolphin-mixtral1x22b |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 8 |
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micro_batch_size: 1 |
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num_epochs: 3 |
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optimizer: adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 1e-5 |
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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: true |
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early_stopping_patience: |
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resume_from_checkpoint: /workspace/axolotl2/axolotl/1x22b-out/checkpoint-507 |
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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: 10 |
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evals_per_epoch: 4 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 4 |
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save_total_limit: 2 |
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debug: |
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.01 |
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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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bos_token: "<s>" |
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# pad_token: "<unk>" |
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unk_token: "<unk>" |
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tokens: |
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- "<|im_start|>" |
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``` |
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</details><br> |
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# 1x22b-out |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 8 |
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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: 10 |
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- num_epochs: 3 |
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### Training results |
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|
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| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.9818 | 0.0015 | 1 | 0.9854 | |
|
| 0.4783 | 0.2499 | 169 | 0.5042 | |
|
| 0.464 | 0.4997 | 338 | 0.4755 | |
|
| 0.4561 | 0.7496 | 507 | 0.4593 | |
|
| 0.3981 | 0.9994 | 676 | 0.4553 | |
|
| 0.3725 | 1.2378 | 845 | 0.4525 | |
|
| 0.3624 | 1.4877 | 1014 | 0.4457 | |
|
| 0.359 | 1.7376 | 1183 | 0.4393 | |
|
| 0.375 | 1.9874 | 1352 | 0.4345 | |
|
| 0.2899 | 2.2260 | 1521 | 0.4488 | |
|
| 0.2848 | 2.4759 | 1690 | 0.4473 | |
|
| 0.2935 | 2.7257 | 1859 | 0.4470 | |
|
| 0.2065 | 2.9756 | 2028 | 0.4572 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
