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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Qwen/Qwen2.5-32B |
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datasets: |
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- anthracite-org/kalo-opus-instruct-22k-no-refusal |
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- Nopm/Opus_WritingStruct |
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- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned |
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- Gryphe/Sonnet3.5-Charcard-Roleplay |
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- Gryphe/ChatGPT-4o-Writing-Prompts |
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- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned |
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- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned |
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- nothingiisreal/Reddit-Dirty-And-WritingPrompts |
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- allura-org/Celeste-1.x-data-mixture |
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- cognitivecomputations/dolphin-2.9.3 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: EVA-Qwen2.5-32B-SFFT-v0.1 |
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results: [] |
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--- |
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# This repo contains the copy of the original quantized to EXL2. Original: [EVA-UNIT-01/EVA-Qwen2.5-32B-v0.1](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-32B-v0.1) |
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# EVA Qwen2.5-32B v0.1 |
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<p> |
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A RP/storywriting specialist model, full-parameter finetune of Qwen2.5-32B on mixture of synthetic and natural data.<br> |
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It uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and "flavor" of the resulting model.<br> |
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</p> |
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<p>Version notes for 0.1: Additional round of cleaning for the datasets, new subsets of 4o-WritingPrompts and Charcards, picking the most diverse samples from them, plus added a small subset of SystemChat2.0 to improve instruction following and sliglthy increased sequence length. Additionally, fixed the training config mistake from 32B 0.0, layernorm layers stay frozen this time. Unfreezing them caused positivity bias to appear in 32B 0.0 for some reason.</p> |
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<p> |
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<p>Prompt format is ChatML.</p><br> |
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<h3>Recommended sampler values:</h3> |
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<ul> |
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<li>Temperature: 1</li> |
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<li>Typical-P: 0.9</li> |
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<li>Min-P: 0.05</li> |
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<li>Top-A: 0.2</li> |
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<li>Repetition Penalty: 1.03</li> |
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</ul> |
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<h3>Recommended SillyTavern presets (via CalamitousFelicitousness):</h3> |
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- [Context](https://huggingface.co/EVA-UNIT-01/EVA-Yi-1.5-9B-32K-V1/blob/main/%5BChatML%5D%20Roleplay-v1.9%20Context.json) |
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- [Instruct and System Prompt](https://huggingface.co/EVA-UNIT-01/EVA-Yi-1.5-9B-32K-V1/blob/main/%5BChatML%5D%20Roleplay-v1.9%20Instruct.json) |
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</p> |
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<p> |
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<br> |
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<h3> |
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Training data: |
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</h3> |
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<ul> |
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<li>Celeste 70B 0.1 data mixture minus Opus Instruct subset. See that model's <a href=https://huggingface.co/nothingiisreal/L3.1-70B-Celeste-V0.1-BF16>card</a> for details.</li> |
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<li>Kalomaze's Opus_Instruct_25k dataset, filtered for refusals.</li> |
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<li>A subset (1k rows) of ChatGPT-4o-WritingPrompts by Gryphe</li> |
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<li>A subset (2k rows) of Sonnet3.5-Charcards-Roleplay by Gryphe</li> |
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<li>Synthstruct and SynthRP datasets by Epiculous</li> |
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<li>A subset from Dolphin-2.9.3, including filtered version of not_samantha and a small subset of systemchat.</li> |
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</ul> |
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<h3> |
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Training time and hardware: |
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</h3> |
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<ul><li>7 hours on 8xH100 SXM, provided by <a href=https://featherless.ai/>FeatherlessAI</a></li></ul><br> |
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</p> |
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<p>Model was trained by Kearm and Auri.</p> |
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<h4>Special thanks:</h4><ul> |
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<li><b>to <a href=https://featherless.ai/>FeatherlessAI</a> for generously providing 8xH100 SXM node for training of this model</b></li> |
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<li>to Gryphe, Lemmy, Kalomaze, Nopm, Epiculous and CogninitiveComputations for the data</li> |
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<li>and to Allura-org for support, feedback, beta-testing and doing quality control of EVA models.</li></ul> |
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: Qwen/Qwen2.5-32B |
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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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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_swiglu: true |
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liger_fused_linear_cross_entropy: true |
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# plugins: |
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# - axolotl.integrations.spectrum.SpectrumPlugin |
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# spectrum_top_fraction: 0.5 |
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# # Optional if using a pre-scanned model as your base_model. Useful if using a model mirror |
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# spectrum_model_name: Qwen/Qwen2.5-32B |
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datasets: |
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- path: datasets/deduped_Synthstruct-Gens_processed_sharegpt_converted_cleaned.jsonl |
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type: sharegpt |
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- path: datasets/opus-instruct-22k-no_refusals-filtered.jsonl |
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type: sharegpt |
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- path: datasets/Celeste_Filtered.jsonl |
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type: sharegpt |
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- path: datasets/Sonnet3-5-charcard-names-filtered-sharegpt.jsonl |
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type: sharegpt |
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- path: datasets/deduped_SynthRP-Gens_processed_09-25-2024-ShareGPT_converted_cleaned.jsonl |
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type: sharegpt |
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- path: datasets/Gryphe-4o-WP-filtered-sharegpt.jsonl |
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type: sharegpt |
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- path: datasets/deduped_not_samantha_norefusals.jsonl |
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type: sharegpt |
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- path: datasets/SystemChat_subset_filtered_sharegpt.jsonl |
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type: sharegpt |
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chat_template: chatml |
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shuffle_merged_datasets: true |
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val_set_size: 0.001 |
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output_dir: ./EVA-Qwen2.5-32B-SFFT-v0.1 |
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sequence_len: 9216 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: true |
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# adapter: qlora |
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# lora_model_dir: |
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# lora_r: 64 |
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# lora_alpha: 128 |
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# lora_dropout: 0.05 |
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# lora_target_linear: true |
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# peft_use_dora: 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.63.mlp.down_proj |
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- model.layers.49.mlp.down_proj |
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- model.layers.48.mlp.down_proj |
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- model.layers.45.mlp.down_proj |
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- model.layers.44.mlp.down_proj |
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- model.layers.47.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.8.mlp.down_proj |
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- model.layers.11.mlp.down_proj |
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- model.layers.19.mlp.down_proj |
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- model.layers.35.mlp.down_proj |
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- model.layers.20.mlp.down_proj |
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- model.layers.52.mlp.down_proj |
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- model.layers.39.mlp.down_proj |
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- model.layers.62.mlp.down_proj |
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- model.layers.50.mlp.down_proj |
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- model.layers.29.mlp.down_proj |
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- model.layers.16.mlp.down_proj |
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- model.layers.28.mlp.down_proj |
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- model.layers.53.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.7.mlp.down_proj |
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- model.layers.36.mlp.down_proj |
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- model.layers.12.mlp.down_proj |
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- model.layers.18.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.14.mlp.down_proj |
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- model.layers.13.mlp.down_proj |
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# mlp.gate_proj layers |
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- model.layers.43.mlp.gate_proj |
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- model.layers.61.mlp.gate_proj |
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- model.layers.60.mlp.gate_proj |
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- model.layers.44.mlp.gate_proj |
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- model.layers.62.mlp.gate_proj |
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- model.layers.28.mlp.gate_proj |
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- model.layers.29.mlp.gate_proj |
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- model.layers.45.mlp.gate_proj |
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- model.layers.37.mlp.gate_proj |
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- model.layers.35.mlp.gate_proj |
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- model.layers.59.mlp.gate_proj |
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- model.layers.36.mlp.gate_proj |
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- model.layers.30.mlp.gate_proj |
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- model.layers.48.mlp.gate_proj |
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- model.layers.38.mlp.gate_proj |
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- model.layers.27.mlp.gate_proj |
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- model.layers.31.mlp.gate_proj |
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- model.layers.34.mlp.gate_proj |
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- model.layers.58.mlp.gate_proj |
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- model.layers.33.mlp.gate_proj |
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- model.layers.39.mlp.gate_proj |
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- model.layers.26.mlp.gate_proj |
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- model.layers.32.mlp.gate_proj |
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- model.layers.46.mlp.gate_proj |
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- model.layers.42.mlp.gate_proj |
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- model.layers.49.mlp.gate_proj |
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- model.layers.57.mlp.gate_proj |
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- model.layers.50.mlp.gate_proj |
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- model.layers.47.mlp.gate_proj |
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- model.layers.56.mlp.gate_proj |
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- model.layers.63.mlp.gate_proj |
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- model.layers.55.mlp.gate_proj |
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# mlp.up_proj layers |
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- model.layers.61.mlp.up_proj |
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- model.layers.60.mlp.up_proj |
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- model.layers.32.mlp.up_proj |
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- model.layers.59.mlp.up_proj |
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- model.layers.58.mlp.up_proj |
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- model.layers.57.mlp.up_proj |
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- model.layers.44.mlp.up_proj |
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- model.layers.28.mlp.up_proj |
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- model.layers.35.mlp.up_proj |
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- model.layers.36.mlp.up_proj |
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- model.layers.29.mlp.up_proj |
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- model.layers.31.mlp.up_proj |
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- model.layers.34.mlp.up_proj |
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- model.layers.55.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.53.mlp.up_proj |
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- model.layers.43.mlp.up_proj |
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- model.layers.56.mlp.up_proj |
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- model.layers.33.mlp.up_proj |
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- model.layers.54.mlp.up_proj |
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- model.layers.62.mlp.up_proj |
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- model.layers.27.mlp.up_proj |
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- model.layers.51.mlp.up_proj |
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- model.layers.52.mlp.up_proj |
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- model.layers.37.mlp.up_proj |
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- model.layers.45.mlp.up_proj |
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- model.layers.26.mlp.up_proj |
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- model.layers.42.mlp.up_proj |
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- model.layers.50.mlp.up_proj |
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- model.layers.48.mlp.up_proj |
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- model.layers.39.mlp.up_proj |
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# self_attn.k_proj layers |
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- model.layers.63.self_attn.k_proj |
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- model.layers.55.self_attn.k_proj |
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- model.layers.60.self_attn.k_proj |
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- model.layers.7.self_attn.k_proj |
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- model.layers.12.self_attn.k_proj |
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- model.layers.13.self_attn.k_proj |
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- model.layers.57.self_attn.k_proj |
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- model.layers.29.self_attn.k_proj |
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- model.layers.14.self_attn.k_proj |
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- model.layers.51.self_attn.k_proj |
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- model.layers.53.self_attn.k_proj |
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- model.layers.54.self_attn.k_proj |
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- model.layers.22.self_attn.k_proj |
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- model.layers.61.self_attn.k_proj |
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- model.layers.18.self_attn.k_proj |
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- model.layers.30.self_attn.k_proj |
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- model.layers.9.self_attn.k_proj |
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- model.layers.24.self_attn.k_proj |
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- model.layers.23.self_attn.k_proj |
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- model.layers.25.self_attn.k_proj |
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- model.layers.10.self_attn.k_proj |
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- model.layers.58.self_attn.k_proj |
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- model.layers.56.self_attn.k_proj |
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- model.layers.15.self_attn.k_proj |
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- model.layers.32.self_attn.k_proj |
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- model.layers.28.self_attn.k_proj |
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- model.layers.8.self_attn.k_proj |
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- model.layers.59.self_attn.k_proj |
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- model.layers.11.self_attn.k_proj |
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- model.layers.48.self_attn.k_proj |
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- model.layers.16.self_attn.k_proj |
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- model.layers.50.self_attn.k_proj |
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# self_attn.o_proj layers |
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- model.layers.15.self_attn.o_proj |
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- model.layers.23.self_attn.o_proj |
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- model.layers.31.self_attn.o_proj |
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- model.layers.30.self_attn.o_proj |
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- model.layers.18.self_attn.o_proj |
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- model.layers.24.self_attn.o_proj |
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- model.layers.17.self_attn.o_proj |
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- model.layers.28.self_attn.o_proj |
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- model.layers.34.self_attn.o_proj |
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- model.layers.33.self_attn.o_proj |
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- model.layers.25.self_attn.o_proj |
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- model.layers.12.self_attn.o_proj |
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- model.layers.14.self_attn.o_proj |
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- model.layers.29.self_attn.o_proj |
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- model.layers.16.self_attn.o_proj |
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- model.layers.26.self_attn.o_proj |
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- model.layers.22.self_attn.o_proj |
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- model.layers.27.self_attn.o_proj |
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- model.layers.35.self_attn.o_proj |
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- model.layers.20.self_attn.o_proj |
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- model.layers.13.self_attn.o_proj |
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- model.layers.36.self_attn.o_proj |
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- model.layers.19.self_attn.o_proj |
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- model.layers.37.self_attn.o_proj |
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- model.layers.21.self_attn.o_proj |
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- model.layers.11.self_attn.o_proj |
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- model.layers.54.self_attn.o_proj |
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- model.layers.5.self_attn.o_proj |
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- model.layers.38.self_attn.o_proj |
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- model.layers.6.self_attn.o_proj |
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- model.layers.8.self_attn.o_proj |
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- model.layers.9.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.2.self_attn.q_proj |
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- model.layers.3.self_attn.q_proj |
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- model.layers.45.self_attn.q_proj |
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- model.layers.54.self_attn.q_proj |
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- model.layers.35.self_attn.q_proj |
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- model.layers.48.self_attn.q_proj |
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- model.layers.61.self_attn.q_proj |
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- model.layers.52.self_attn.q_proj |
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- model.layers.50.self_attn.q_proj |
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- model.layers.60.self_attn.q_proj |
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- model.layers.56.self_attn.q_proj |
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- model.layers.58.self_attn.q_proj |
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- model.layers.42.self_attn.q_proj |
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- model.layers.59.self_attn.q_proj |
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- model.layers.44.self_attn.q_proj |
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- model.layers.55.self_attn.q_proj |
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- model.layers.57.self_attn.q_proj |
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- model.layers.41.self_attn.q_proj |
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- model.layers.36.self_attn.q_proj |
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- model.layers.39.self_attn.q_proj |
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- model.layers.4.self_attn.q_proj |
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- model.layers.43.self_attn.q_proj |
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- model.layers.34.self_attn.q_proj |
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- model.layers.46.self_attn.q_proj |
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- model.layers.49.self_attn.q_proj |
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- model.layers.40.self_attn.q_proj |
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- model.layers.25.self_attn.q_proj |
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- model.layers.51.self_attn.q_proj |
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- model.layers.17.self_attn.q_proj |
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- model.layers.37.self_attn.q_proj |
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- model.layers.53.self_attn.q_proj |
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# self_attn.v_proj layers |
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- model.layers.55.self_attn.v_proj |
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- model.layers.31.self_attn.v_proj |
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- model.layers.47.self_attn.v_proj |
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- model.layers.45.self_attn.v_proj |
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- model.layers.49.self_attn.v_proj |
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- model.layers.48.self_attn.v_proj |
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- model.layers.15.self_attn.v_proj |
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- model.layers.30.self_attn.v_proj |
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- model.layers.7.self_attn.v_proj |
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- model.layers.44.self_attn.v_proj |
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- model.layers.29.self_attn.v_proj |
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- model.layers.51.self_attn.v_proj |
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- model.layers.50.self_attn.v_proj |
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- model.layers.14.self_attn.v_proj |
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- model.layers.54.self_attn.v_proj |
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- model.layers.32.self_attn.v_proj |
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- model.layers.43.self_attn.v_proj |
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- model.layers.10.self_attn.v_proj |
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- model.layers.46.self_attn.v_proj |
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- model.layers.38.self_attn.v_proj |
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- model.layers.57.self_attn.v_proj |
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- model.layers.22.self_attn.v_proj |
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- model.layers.39.self_attn.v_proj |
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- model.layers.6.self_attn.v_proj |
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- model.layers.23.self_attn.v_proj |
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- model.layers.58.self_attn.v_proj |
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- model.layers.53.self_attn.v_proj |
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- model.layers.40.self_attn.v_proj |
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- model.layers.24.self_attn.v_proj |
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- model.layers.9.self_attn.v_proj |
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- model.layers.25.self_attn.v_proj |
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- model.layers.5.self_attn.v_proj |
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wandb_project: EVA-Qwen2.5-32B-SFFT-v0.1 |
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wandb_entity: |
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wandb_watch: |
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wandb_name: Unit-01 |
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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: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.00005 |
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max_grad_norm: 3 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: "unsloth" |
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# gradient_checkpointing_kwargs: |
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# use_reentrant: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 20 |
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evals_per_epoch: 4 |
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saves_per_epoch: 2 |
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save_safetensors: true |
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hub_model_id: |
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hub_strategy: |
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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.1 |
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# fsdp: |
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# - full_shard |
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# - auto_wrap |
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# fsdp_config: |
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# fsdp_limit_all_gathers: true |
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# fsdp_sync_module_states: false |
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# fsdp_offload_params: true |
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# fsdp_cpu_ram_efficient_loading: true |
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# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP |
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# fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer |
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# fsdp_activation_checkpointing: true |
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# fsdp_state_dict_type: SHARDED_STATE_DICT # Changed from FULL_STATE_DICT |
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# fsdp_sharding_strategy: FULL_SHARD |
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# fsdp_forward_prefetch: false # Added |
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# fsdp_backward_prefetch: "BACKWARD_PRE" # Added |
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# fsdp_backward_prefetch_limit: 1 # Added |
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# fsdp_mixed_precision: BF16 # Added |
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``` |
|
|
|
</details> |
