Triangle104
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Update README.md
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README.md
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@@ -26,6 +26,398 @@ model-index:
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This model was converted to GGUF format from [`EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2`](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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This model was converted to GGUF format from [`EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2`](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2) for more details on the model.
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---
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Model details:
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-
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A RP/storywriting specialist model, full-parameter finetune of Qwen2.5-14B on mixture of synthetic and natural data.
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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.
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Version notes for 0.2: Now using the refined dataset from 32B 0.2. Major improvements in coherence, instruction following and long-context comprehension over 14B v0.1.
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Prompt format is ChatML.
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Recommended sampler values:
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Temperature: 0.8
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Min-P: 0.05
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Top-A: 0.3
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Repetition Penalty: 1.03
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Recommended SillyTavern presets (via CalamitousFelicitousness):
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Context
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Instruct and System Prompt
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Training data:
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Celeste 70B 0.1 data mixture minus Opus Instruct subset. See that model's card for details.
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Kalomaze's Opus_Instruct_25k dataset, filtered for refusals.
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A subset (1k rows) of ChatGPT-4o-WritingPrompts by Gryphe
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A subset (2k rows) of Sonnet3.5-Charcards-Roleplay by Gryphe
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Synthstruct and SynthRP datasets by Epiculous
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A subset from Dolphin-2.9.3, including filtered version of not_samantha and a small subset of systemchat.
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Training time and hardware:
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3 hours on 8xH100 SXM, provided by FeatherlessAI
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Model was created by Kearm, Auri and Cahvay.
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Special thanks:
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to Cahvay for his work on investigating and reprocessing the corrupted dataset, removing the single biggest source of data poisoning.
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to FeatherlessAI for generously providing 8xH100 SXM node for training of this model
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to Gryphe, Lemmy, Kalomaze, Nopm, Epiculous and CogninitiveComputations for the data
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and to Allura-org for support, feedback, beta-testing and doing quality control of EVA models.
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Built with Axolotl
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See axolotl config
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axolotl version: 0.4.1
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base_model: Qwen/Qwen2.5-14B
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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/Celeste_Filtered_utf8fix.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/deduped_SynthRP-Gens_processed_ShareGPT_converted_cleaned.jsonl
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type: sharegpt
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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/Gryphe-4o-WP-filtered-sharegpt_utf8fix.jsonl
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type: sharegpt
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- path: datasets/opus-instruct-22k-no_refusals-filtered_utf8fix.jsonl
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type: sharegpt
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- path: datasets/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl
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type: sharegpt
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- path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.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-Qwen2.5-14B-SFFT-v0.2
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sequence_len: 10240
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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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base_model: Qwen/Qwen2.5-14B
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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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datasets:
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- path: datasets/Celeste_Filtered_utf8fix.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/deduped_SynthRP-Gens_processed_ShareGPT_converted_cleaned.jsonl
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type: sharegpt
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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/Gryphe-4o-WP-filtered-sharegpt_utf8fix.jsonl
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type: sharegpt
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- path: datasets/opus-instruct-22k-no_refusals-filtered_utf8fix.jsonl
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type: sharegpt
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- path: datasets/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl
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type: sharegpt
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- path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.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: 0.005
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output_dir: ./EVA-Qwen2.5-14B-SFFT-v0.2
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sequence_len: 10240
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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: 32
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# lora_alpha: 16
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# lora_dropout: 0.05
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# lora_target_linear: true
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# 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.1.mlp.down_proj
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- model.layers.35.mlp.down_proj
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- model.layers.38.mlp.down_proj
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- model.layers.37.mlp.down_proj
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- model.layers.36.mlp.down_proj
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- model.layers.15.mlp.down_proj
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- model.layers.11.mlp.down_proj
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- model.layers.12.mlp.down_proj
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- model.layers.34.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.9.mlp.down_proj
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- model.layers.41.mlp.down_proj
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- model.layers.33.mlp.down_proj
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- model.layers.43.mlp.down_proj
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- model.layers.40.mlp.down_proj
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- model.layers.13.mlp.down_proj
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- model.layers.8.mlp.down_proj
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- model.layers.39.mlp.down_proj
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- model.layers.10.mlp.down_proj
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- model.layers.14.mlp.down_proj
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- model.layers.16.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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# mlp.gate_proj layers
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- model.layers.1.mlp.gate_proj
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- model.layers.44.mlp.gate_proj
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- model.layers.46.mlp.gate_proj
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- model.layers.45.mlp.gate_proj
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- model.layers.43.mlp.gate_proj
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- model.layers.47.mlp.gate_proj
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- model.layers.42.mlp.gate_proj
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- model.layers.32.mlp.gate_proj
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- model.layers.27.mlp.gate_proj
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- model.layers.33.mlp.gate_proj
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- model.layers.28.mlp.gate_proj
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- model.layers.39.mlp.gate_proj
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- model.layers.41.mlp.gate_proj
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- model.layers.40.mlp.gate_proj
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- model.layers.30.mlp.gate_proj
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- model.layers.29.mlp.gate_proj
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- model.layers.31.mlp.gate_proj
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- model.layers.37.mlp.gate_proj
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- model.layers.26.mlp.gate_proj
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- model.layers.10.mlp.gate_proj
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- model.layers.38.mlp.gate_proj
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- model.layers.36.mlp.gate_proj
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- model.layers.12.mlp.gate_proj
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- model.layers.13.mlp.gate_proj
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# mlp.up_proj layers
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- model.layers.1.mlp.up_proj
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- model.layers.13.mlp.up_proj
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- model.layers.11.mlp.up_proj
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- model.layers.14.mlp.up_proj
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- model.layers.15.mlp.up_proj
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- model.layers.12.mlp.up_proj
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- model.layers.8.mlp.up_proj
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- model.layers.16.mlp.up_proj
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- model.layers.9.mlp.up_proj
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- model.layers.19.mlp.up_proj
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- model.layers.10.mlp.up_proj
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- model.layers.7.mlp.up_proj
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- model.layers.17.mlp.up_proj
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- model.layers.20.mlp.up_proj
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- model.layers.21.mlp.up_proj
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- model.layers.18.mlp.up_proj
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- model.layers.37.mlp.up_proj
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- model.layers.38.mlp.up_proj
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- model.layers.39.mlp.up_proj
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- model.layers.42.mlp.up_proj
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- model.layers.41.mlp.up_proj
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- model.layers.27.mlp.up_proj
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- model.layers.28.mlp.up_proj
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- model.layers.36.mlp.up_proj
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# self_attn.k_proj layers
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- model.layers.47.self_attn.k_proj
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- model.layers.39.self_attn.k_proj
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- model.layers.41.self_attn.k_proj
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- model.layers.37.self_attn.k_proj
|
267 |
+
- model.layers.35.self_attn.k_proj
|
268 |
+
- model.layers.44.self_attn.k_proj
|
269 |
+
- model.layers.38.self_attn.k_proj
|
270 |
+
- model.layers.14.self_attn.k_proj
|
271 |
+
- model.layers.7.self_attn.k_proj
|
272 |
+
- model.layers.12.self_attn.k_proj
|
273 |
+
- model.layers.11.self_attn.k_proj
|
274 |
+
- model.layers.32.self_attn.k_proj
|
275 |
+
- model.layers.10.self_attn.k_proj
|
276 |
+
- model.layers.8.self_attn.k_proj
|
277 |
+
- model.layers.6.self_attn.k_proj
|
278 |
+
- model.layers.9.self_attn.k_proj
|
279 |
+
- model.layers.45.self_attn.k_proj
|
280 |
+
- model.layers.42.self_attn.k_proj
|
281 |
+
- model.layers.40.self_attn.k_proj
|
282 |
+
- model.layers.5.self_attn.k_proj
|
283 |
+
- model.layers.0.self_attn.k_proj
|
284 |
+
- model.layers.33.self_attn.k_proj
|
285 |
+
- model.layers.34.self_attn.k_proj
|
286 |
+
- model.layers.13.self_attn.k_proj
|
287 |
+
# self_attn.o_proj layers
|
288 |
+
- model.layers.12.self_attn.o_proj
|
289 |
+
- model.layers.5.self_attn.o_proj
|
290 |
+
- model.layers.14.self_attn.o_proj
|
291 |
+
- model.layers.16.self_attn.o_proj
|
292 |
+
- model.layers.20.self_attn.o_proj
|
293 |
+
- model.layers.13.self_attn.o_proj
|
294 |
+
- model.layers.11.self_attn.o_proj
|
295 |
+
- model.layers.4.self_attn.o_proj
|
296 |
+
- model.layers.6.self_attn.o_proj
|
297 |
+
- model.layers.19.self_attn.o_proj
|
298 |
+
- model.layers.7.self_attn.o_proj
|
299 |
+
- model.layers.18.self_attn.o_proj
|
300 |
+
- model.layers.8.self_attn.o_proj
|
301 |
+
- model.layers.38.self_attn.o_proj
|
302 |
+
- model.layers.15.self_attn.o_proj
|
303 |
+
- model.layers.17.self_attn.o_proj
|
304 |
+
- model.layers.9.self_attn.o_proj
|
305 |
+
- model.layers.10.self_attn.o_proj
|
306 |
+
- model.layers.21.self_attn.o_proj
|
307 |
+
- model.layers.28.self_attn.o_proj
|
308 |
+
- model.layers.32.self_attn.o_proj
|
309 |
+
- model.layers.35.self_attn.o_proj
|
310 |
+
- model.layers.39.self_attn.o_proj
|
311 |
+
- model.layers.3.self_attn.o_proj
|
312 |
+
# self_attn.q_proj layers
|
313 |
+
- model.layers.1.self_attn.q_proj
|
314 |
+
- model.layers.2.self_attn.q_proj
|
315 |
+
- model.layers.3.self_attn.q_proj
|
316 |
+
- model.layers.44.self_attn.q_proj
|
317 |
+
- model.layers.29.self_attn.q_proj
|
318 |
+
- model.layers.45.self_attn.q_proj
|
319 |
+
- model.layers.43.self_attn.q_proj
|
320 |
+
- model.layers.32.self_attn.q_proj
|
321 |
+
- model.layers.38.self_attn.q_proj
|
322 |
+
- model.layers.19.self_attn.q_proj
|
323 |
+
- model.layers.42.self_attn.q_proj
|
324 |
+
- model.layers.34.self_attn.q_proj
|
325 |
+
- model.layers.36.self_attn.q_proj
|
326 |
+
- model.layers.40.self_attn.q_proj
|
327 |
+
- model.layers.26.self_attn.q_proj
|
328 |
+
- model.layers.20.self_attn.q_proj
|
329 |
+
- model.layers.28.self_attn.q_proj
|
330 |
+
- model.layers.39.self_attn.q_proj
|
331 |
+
- model.layers.41.self_attn.q_proj
|
332 |
+
- model.layers.33.self_attn.q_proj
|
333 |
+
- model.layers.35.self_attn.q_proj
|
334 |
+
- model.layers.25.self_attn.q_proj
|
335 |
+
- model.layers.30.self_attn.q_proj
|
336 |
+
- model.layers.27.self_attn.q_proj
|
337 |
+
# self_attn.v_proj layers
|
338 |
+
- model.layers.0.self_attn.v_proj
|
339 |
+
- model.layers.7.self_attn.v_proj
|
340 |
+
- model.layers.39.self_attn.v_proj
|
341 |
+
- model.layers.31.self_attn.v_proj
|
342 |
+
- model.layers.15.self_attn.v_proj
|
343 |
+
- model.layers.10.self_attn.v_proj
|
344 |
+
- model.layers.41.self_attn.v_proj
|
345 |
+
- model.layers.32.self_attn.v_proj
|
346 |
+
- model.layers.6.self_attn.v_proj
|
347 |
+
- model.layers.33.self_attn.v_proj
|
348 |
+
- model.layers.42.self_attn.v_proj
|
349 |
+
- model.layers.29.self_attn.v_proj
|
350 |
+
- model.layers.9.self_attn.v_proj
|
351 |
+
- model.layers.14.self_attn.v_proj
|
352 |
+
- model.layers.35.self_attn.v_proj
|
353 |
+
- model.layers.38.self_attn.v_proj
|
354 |
+
- model.layers.13.self_attn.v_proj
|
355 |
+
- model.layers.30.self_attn.v_proj
|
356 |
+
- model.layers.34.self_attn.v_proj
|
357 |
+
- model.layers.5.self_attn.v_proj
|
358 |
+
- model.layers.28.self_attn.v_proj
|
359 |
+
- model.layers.37.self_attn.v_proj
|
360 |
+
- model.layers.27.self_attn.v_proj
|
361 |
+
- model.layers.11.self_attn.v_proj
|
362 |
+
|
363 |
+
wandb_project: EVA-Qwen2.5-14B-SFFT-v0.2
|
364 |
+
wandb_entity:
|
365 |
+
wandb_watch:
|
366 |
+
wandb_name: Unit-02
|
367 |
+
wandb_log_model:
|
368 |
+
|
369 |
+
gradient_accumulation_steps: 8
|
370 |
+
micro_batch_size: 2
|
371 |
+
num_epochs: 3
|
372 |
+
optimizer: paged_ademamix_8bit
|
373 |
+
lr_scheduler: cosine
|
374 |
+
learning_rate: 0.00005
|
375 |
+
max_grad_norm: 3
|
376 |
+
|
377 |
+
train_on_inputs: false
|
378 |
+
group_by_length: false
|
379 |
+
bf16: auto
|
380 |
+
fp16:
|
381 |
+
tf32: false
|
382 |
+
|
383 |
+
gradient_checkpointing: "unsloth"
|
384 |
+
# gradient_checkpointing_kwargs:
|
385 |
+
# use_reentrant: true
|
386 |
+
early_stopping_patience:
|
387 |
+
resume_from_checkpoint:
|
388 |
+
local_rank:
|
389 |
+
logging_steps: 1
|
390 |
+
xformers_attention:
|
391 |
+
flash_attention: true
|
392 |
+
|
393 |
+
warmup_steps: 20
|
394 |
+
evals_per_epoch: 4
|
395 |
+
saves_per_epoch: 4
|
396 |
+
save_safetensors: true
|
397 |
+
hub_model_id:
|
398 |
+
hub_strategy:
|
399 |
+
debug:
|
400 |
+
deepspeed: deepspeed_configs/zero3_bf16.json
|
401 |
+
weight_decay: 0.1
|
402 |
+
# fsdp:
|
403 |
+
# - full_shard
|
404 |
+
# - auto_wrap
|
405 |
+
# fsdp_config:
|
406 |
+
# fsdp_limit_all_gathers: true
|
407 |
+
# fsdp_sync_module_states: false
|
408 |
+
# fsdp_offload_params: true
|
409 |
+
# fsdp_cpu_ram_efficient_loading: true
|
410 |
+
# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
|
411 |
+
# fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
|
412 |
+
# fsdp_activation_checkpointing: true
|
413 |
+
# fsdp_state_dict_type: SHARDED_STATE_DICT # Changed from FULL_STATE_DICT
|
414 |
+
# fsdp_sharding_strategy: FULL_SHARD
|
415 |
+
# fsdp_forward_prefetch: false # Added
|
416 |
+
# fsdp_backward_prefetch: "BACKWARD_PRE" # Added
|
417 |
+
# fsdp_backward_prefetch_limit: 1 # Added
|
418 |
+
# fsdp_mixed_precision: BF16 # Added
|
419 |
+
|
420 |
+
---
|
421 |
## Use with llama.cpp
|
422 |
Install llama.cpp through brew (works on Mac and Linux)
|
423 |
|