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--- |
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license: llama3 |
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base_model: meta-llama/Meta-Llama-3-70B |
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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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- Locutusque/function-calling-chatml |
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- internlm/Agent-FLAN |
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--- |
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# Dolphin 2.9.1 Llama 3 70b 🐬 |
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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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We have retrained our LLama-3-70b fine tune to address behavioral issues in the initial 2.9 dataset. Specifically, Systemchat was causing the model to be *too* reliant on the system prompt. Additionally, it had an occasional quirk that would cause the model to overly reference the system prompt. We also found generation length was at times not sufficient for any given task. We identified the culprit as Ultrachat. Accounting for these concerns, we removed systemchat and ultrachat from the dataset. It is otherwise identical to dolphin-2.9. |
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Our appreciation for the sponsors of Dolphin 2.9.1: |
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- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xL40S node |
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- [OnDemand](https://on-demand.io/) - provided inference sponsorship |
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This model is based on Llama-3-70b, and is governed by [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](LICENSE) |
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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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It took 3 days on an 8x H100 provided by Crusoe Cloud |
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This model was trained FFT on parameters selected by [Laser Scanner](https://github.com/cognitivecomputations/laserRMT/blob/main/laser_scanner.py), using ChatML prompt template format. |
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example: |
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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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Dolphin-2.9.1 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 according to Meta's Llama license. We 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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## Evals |
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## Training |
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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: meta-llama/Meta-Llama-3-70B |
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model_type: LlamaForCausalLM |
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tokenizer_type: AutoTokenizer |
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load_in_8bit: false |
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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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# adapter: qlora |
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# lora_r: 128 |
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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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# mlp.down_proj layers |
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- model.layers.40.mlp.down_proj |
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- model.layers.44.mlp.down_proj |
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- model.layers.45.mlp.down_proj |
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- model.layers.46.mlp.down_proj |
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- model.layers.43.mlp.down_proj |
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- model.layers.52.mlp.down_proj |
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- model.layers.47.mlp.down_proj |
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- model.layers.48.mlp.down_proj |
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- model.layers.39.mlp.down_proj |
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- model.layers.49.mlp.down_proj |
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- model.layers.38.mlp.down_proj |
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- model.layers.53.mlp.down_proj |
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- model.layers.41.mlp.down_proj |
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- model.layers.35.mlp.down_proj |
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- model.layers.51.mlp.down_proj |
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- model.layers.42.mlp.down_proj |
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- model.layers.37.mlp.down_proj |
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- model.layers.50.mlp.down_proj |
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- model.layers.60.mlp.down_proj |
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- model.layers.76.mlp.down_proj |
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- model.layers.54.mlp.down_proj |
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- model.layers.36.mlp.down_proj |
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- model.layers.57.mlp.down_proj |
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- model.layers.56.mlp.down_proj |
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- model.layers.55.mlp.down_proj |
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- model.layers.77.mlp.down_proj |
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- model.layers.59.mlp.down_proj |
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- model.layers.61.mlp.down_proj |
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- model.layers.58.mlp.down_proj |
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- model.layers.65.mlp.down_proj |
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- model.layers.75.mlp.down_proj |
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- model.layers.64.mlp.down_proj |
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- model.layers.62.mlp.down_proj |
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- model.layers.68.mlp.down_proj |
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- model.layers.19.mlp.down_proj |
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- model.layers.66.mlp.down_proj |
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# mlp.gate_proj layers |
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- model.layers.70.mlp.gate_proj |
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- model.layers.71.mlp.gate_proj |
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- model.layers.67.mlp.gate_proj |
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- model.layers.58.mlp.gate_proj |
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- model.layers.55.mlp.gate_proj |
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- model.layers.57.mlp.gate_proj |
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- model.layers.56.mlp.gate_proj |
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- model.layers.66.mlp.gate_proj |
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- model.layers.72.mlp.gate_proj |
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- model.layers.69.mlp.gate_proj |
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- model.layers.52.mlp.gate_proj |
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- model.layers.54.mlp.gate_proj |
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- model.layers.62.mlp.gate_proj |
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- model.layers.60.mlp.gate_proj |
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- model.layers.74.mlp.gate_proj |
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- model.layers.59.mlp.gate_proj |
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- model.layers.68.mlp.gate_proj |
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- model.layers.61.mlp.gate_proj |
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- model.layers.73.mlp.gate_proj |
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- model.layers.53.mlp.gate_proj |
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- model.layers.51.mlp.gate_proj |
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- model.layers.63.mlp.gate_proj |
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- model.layers.48.mlp.gate_proj |
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- model.layers.49.mlp.gate_proj |
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- model.layers.64.mlp.gate_proj |
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- model.layers.50.mlp.gate_proj |
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- model.layers.65.mlp.gate_proj |
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- model.layers.47.mlp.gate_proj |
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- model.layers.44.mlp.gate_proj |
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- model.layers.45.mlp.gate_proj |
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- model.layers.75.mlp.gate_proj |
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- model.layers.46.mlp.gate_proj |
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- model.layers.43.mlp.gate_proj |
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- model.layers.77.mlp.gate_proj |
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- model.layers.41.mlp.gate_proj |
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- model.layers.42.mlp.gate_proj |
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# mlp.up_proj layers |
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- model.layers.70.mlp.up_proj |
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- model.layers.67.mlp.up_proj |
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- model.layers.66.mlp.up_proj |
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- model.layers.69.mlp.up_proj |
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- model.layers.62.mlp.up_proj |
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- model.layers.65.mlp.up_proj |
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- model.layers.63.mlp.up_proj |
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- model.layers.68.mlp.up_proj |
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- model.layers.71.mlp.up_proj |
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- model.layers.64.mlp.up_proj |
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- model.layers.61.mlp.up_proj |
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- model.layers.58.mlp.up_proj |
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- model.layers.59.mlp.up_proj |
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- model.layers.57.mlp.up_proj |
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- model.layers.55.mlp.up_proj |
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- model.layers.72.mlp.up_proj |
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- model.layers.54.mlp.up_proj |
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- model.layers.60.mlp.up_proj |
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- model.layers.56.mlp.up_proj |
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- model.layers.73.mlp.up_proj |
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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.53.mlp.up_proj |
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- model.layers.74.mlp.up_proj |
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- model.layers.52.mlp.up_proj |
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- model.layers.49.mlp.up_proj |
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- model.layers.30.mlp.up_proj |
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- model.layers.34.mlp.up_proj |
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- model.layers.47.mlp.up_proj |
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- model.layers.46.mlp.up_proj |
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- model.layers.48.mlp.up_proj |
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- model.layers.38.mlp.up_proj |
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- model.layers.45.mlp.up_proj |
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- model.layers.43.mlp.up_proj |
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- model.layers.29.mlp.up_proj |
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- model.layers.42.mlp.up_proj |
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# self_attn.k_proj layers |
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- model.layers.72.self_attn.k_proj |
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- model.layers.75.self_attn.k_proj |
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- model.layers.71.self_attn.k_proj |
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- model.layers.74.self_attn.k_proj |
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- model.layers.44.self_attn.k_proj |
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- model.layers.31.self_attn.k_proj |
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- model.layers.33.self_attn.k_proj |
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- model.layers.34.self_attn.k_proj |
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- model.layers.76.self_attn.k_proj |
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- model.layers.78.self_attn.k_proj |
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- model.layers.77.self_attn.k_proj |
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- model.layers.22.self_attn.k_proj |
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- model.layers.18.self_attn.k_proj |
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- model.layers.60.self_attn.k_proj |
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- model.layers.17.self_attn.k_proj |
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- model.layers.56.self_attn.k_proj |
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- model.layers.2.self_attn.k_proj |
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- model.layers.21.self_attn.k_proj |
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- model.layers.19.self_attn.k_proj |
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- model.layers.23.self_attn.k_proj |
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- model.layers.52.self_attn.k_proj |
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- model.layers.35.self_attn.k_proj |
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- model.layers.73.self_attn.k_proj |
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- model.layers.15.self_attn.k_proj |
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- model.layers.27.self_attn.k_proj |
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- model.layers.29.self_attn.k_proj |
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- model.layers.20.self_attn.k_proj |
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- model.layers.28.self_attn.k_proj |
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- model.layers.36.self_attn.k_proj |
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- model.layers.25.self_attn.k_proj |
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- model.layers.37.self_attn.k_proj |
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- model.layers.30.self_attn.k_proj |
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- model.layers.16.self_attn.k_proj |
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- model.layers.32.self_attn.k_proj |
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- model.layers.41.self_attn.k_proj |
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- model.layers.26.self_attn.k_proj |
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# self_attn.o_proj layers |
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- model.layers.50.self_attn.o_proj |
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- model.layers.61.self_attn.o_proj |
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- model.layers.46.self_attn.o_proj |
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- model.layers.53.self_attn.o_proj |
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- model.layers.54.self_attn.o_proj |
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- model.layers.19.self_attn.o_proj |
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- model.layers.42.self_attn.o_proj |
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- model.layers.49.self_attn.o_proj |
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- model.layers.41.self_attn.o_proj |
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- model.layers.68.self_attn.o_proj |
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- model.layers.18.self_attn.o_proj |
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- model.layers.45.self_attn.o_proj |
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- model.layers.11.self_attn.o_proj |
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- model.layers.67.self_attn.o_proj |
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- model.layers.48.self_attn.o_proj |
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- model.layers.51.self_attn.o_proj |
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- model.layers.64.self_attn.o_proj |
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- model.layers.13.self_attn.o_proj |
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- model.layers.14.self_attn.o_proj |
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- model.layers.16.self_attn.o_proj |
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- model.layers.17.self_attn.o_proj |
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- model.layers.47.self_attn.o_proj |
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- model.layers.0.self_attn.o_proj |
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- model.layers.20.self_attn.o_proj |
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- model.layers.63.self_attn.o_proj |
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- model.layers.15.self_attn.o_proj |
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- model.layers.5.self_attn.o_proj |
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- model.layers.21.self_attn.o_proj |
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- model.layers.52.self_attn.o_proj |
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- model.layers.12.self_attn.o_proj |
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- model.layers.10.self_attn.o_proj |
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- model.layers.62.self_attn.o_proj |
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- model.layers.56.self_attn.o_proj |
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- model.layers.22.self_attn.o_proj |
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- model.layers.6.self_attn.o_proj |
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- model.layers.7.self_attn.o_proj |
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# self_attn.q_proj layers |
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- model.layers.2.self_attn.q_proj |
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- model.layers.4.self_attn.q_proj |
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- model.layers.46.self_attn.q_proj |
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- model.layers.5.self_attn.q_proj |
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- model.layers.7.self_attn.q_proj |
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- model.layers.6.self_attn.q_proj |
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- model.layers.9.self_attn.q_proj |
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- model.layers.10.self_attn.q_proj |
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- model.layers.1.self_attn.q_proj |
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- model.layers.18.self_attn.q_proj |
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- model.layers.62.self_attn.q_proj |
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- model.layers.8.self_attn.q_proj |
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- model.layers.15.self_attn.q_proj |
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- model.layers.14.self_attn.q_proj |
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- model.layers.16.self_attn.q_proj |
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- model.layers.31.self_attn.q_proj |
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- model.layers.19.self_attn.q_proj |
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- model.layers.17.self_attn.q_proj |
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- model.layers.33.self_attn.q_proj |
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- model.layers.35.self_attn.q_proj |
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- model.layers.12.self_attn.q_proj |
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- model.layers.21.self_attn.q_proj |
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- model.layers.27.self_attn.q_proj |
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- model.layers.34.self_attn.q_proj |
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- model.layers.13.self_attn.q_proj |
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- model.layers.56.self_attn.q_proj |
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- model.layers.11.self_attn.q_proj |
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- model.layers.52.self_attn.q_proj |
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- model.layers.54.self_attn.q_proj |
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- model.layers.28.self_attn.q_proj |
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- model.layers.30.self_attn.q_proj |
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- model.layers.20.self_attn.q_proj |
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- model.layers.29.self_attn.q_proj |
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- model.layers.37.self_attn.q_proj |
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- model.layers.23.self_attn.q_proj |
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- model.layers.75.self_attn.q_proj |
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# self_attn.v_proj layers |
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- model.layers.11.self_attn.v_proj |
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- model.layers.17.self_attn.v_proj |
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- model.layers.37.self_attn.v_proj |
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- model.layers.40.self_attn.v_proj |
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- model.layers.41.self_attn.v_proj |
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- model.layers.42.self_attn.v_proj |
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- model.layers.43.self_attn.v_proj |
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- model.layers.44.self_attn.v_proj |
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- model.layers.45.self_attn.v_proj |
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- model.layers.46.self_attn.v_proj |
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- model.layers.48.self_attn.v_proj |
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- model.layers.49.self_attn.v_proj |
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- model.layers.50.self_attn.v_proj |
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- model.layers.51.self_attn.v_proj |
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- model.layers.53.self_attn.v_proj |
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- model.layers.54.self_attn.v_proj |
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- model.layers.55.self_attn.v_proj |
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- model.layers.57.self_attn.v_proj |
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- model.layers.58.self_attn.v_proj |
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- model.layers.59.self_attn.v_proj |
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- model.layers.60.self_attn.v_proj |
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- model.layers.61.self_attn.v_proj |
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- model.layers.62.self_attn.v_proj |
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- model.layers.63.self_attn.v_proj |
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- model.layers.64.self_attn.v_proj |
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- model.layers.65.self_attn.v_proj |
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- model.layers.66.self_attn.v_proj |
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- model.layers.67.self_attn.v_proj |
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- model.layers.69.self_attn.v_proj |
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- model.layers.75.self_attn.v_proj |
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- model.layers.18.self_attn.v_proj |
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- model.layers.78.self_attn.v_proj |
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- model.layers.68.self_attn.v_proj |
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- model.layers.47.self_attn.v_proj |
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- model.layers.38.self_attn.v_proj |
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- model.layers.71.self_attn.v_proj |
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# model.norm layers |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.01 |
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output_dir: /workspace/axolotl/llama-70b |
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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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wandb_project: llama-3 |
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wandb_watch: |
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wandb_run_id: |
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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: true |
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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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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 5 |
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evals_per_epoch: 4 |
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eval_table_size: |
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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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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.00 |
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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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</details><br> |
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# workspace/axolotl/llama-70b |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-70B](https://huggingface.co/meta-llama/Meta-Llama-3-70B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4808 |
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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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|
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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: 5 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.7659 | 0.0004 | 1 | 0.7454 | |
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| 0.5006 | 0.2501 | 587 | 0.4817 | |
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| 0.4807 | 0.5002 | 1174 | 0.4698 | |
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| 0.4758 | 0.7503 | 1761 | 0.4627 | |
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| 0.4969 | 1.0004 | 2348 | 0.4558 | |
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| 0.3604 | 1.2346 | 2935 | 0.4635 | |
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| 0.3817 | 1.4847 | 3522 | 0.4572 | |
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| 0.377 | 1.7348 | 4109 | 0.4533 | |
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| 0.3695 | 1.9849 | 4696 | 0.4487 | |
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| 0.2676 | 2.2187 | 5283 | 0.4825 | |
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| 0.255 | 2.4688 | 5870 | 0.4814 | |
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| 0.2851 | 2.7189 | 6457 | 0.4808 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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