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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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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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This is the [llamafile](https://github.com/Mozilla-Ocho/llamafile) for [Dolphin 2.9 Llama 3 8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b). |
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Quick tests show it's good but not as sharp as the base model, using just some few shot prompts looking for precision when asking about history and science. More tests will have to be done to compare this and WizardLM-7B to see how much the finetuning/new EOS did to Llama-3-8B. |
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Notably, [cognitivecomputations](https://huggingface.co/cognitivecomputations) uses a single EOS token. This fixes the garbled output bug. Hooray! It may however prevent some intended behavior of Llama3's internal monologue/thoughts that adds to the model's apparent sharpness. Download Meta's original weights and load manually in python to see what it's capable of as a comparison. We're all awaiting any fixes to llama.cpp and/or the base gguf structure. In the meantime this dolphin is a good fix and excellent work. |
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conversion notes: |
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I converted the original safetensors to f32 to preserve the fidelity from bf16, then quantized ggufs from there. Not sure what most ggufs on hf are doing if they don't say. |
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size notes: |
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Windows users, go for q3-k-m. Others, use the biggest one that works on your machine. FreeBSD users, you're the real heroes. |
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I just copied the original model card this time. |
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## .-=~ Original Model Card ~=-. |
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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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# Dolphin 2.9 Llama 3 8b 🐬 |
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Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations |
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Discord: https://discord.gg/8fbBeC7ZGx |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" /> |
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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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This model is based on Llama-3-8b, 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 2.5 days on 8x L40S provided by Crusoe Cloud |
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This model was trained FFT on all parameters, 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 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. 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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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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[<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-3-8B |
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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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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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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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chat_template: chatml |
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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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sequence_len: 4096 |
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sample_packing: true |
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pad_to_sequence_len: true |
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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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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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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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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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</details><br> |
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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: 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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### Training results |
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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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### Framework versions |
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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 |
