Update README.md
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README.md
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@@ -26,6 +26,442 @@ 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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| 27 |
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
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versatility, creativity and "flavor" of the resulting model.
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+
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Version notes for 0.2: Now using the refined dataset from 32B
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0.2. Major improvements in coherence, instruction following and
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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
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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 CognitiveComputations 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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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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+
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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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+
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# plugins:
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# - axolotl.integrations.spectrum.SpectrumPlugin
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+
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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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+
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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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+
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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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+
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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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+
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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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+
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base_model: Qwen/Qwen2.5-14B
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+
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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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+
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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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| 189 |
+
liger_swiglu: true
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+
liger_fused_linear_cross_entropy: true
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| 191 |
+
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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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+
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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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| 214 |
+
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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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+
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+
# adapter: qlora
|
| 221 |
+
# lora_model_dir:
|
| 222 |
+
# lora_r: 32
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| 223 |
+
# lora_alpha: 16
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| 224 |
+
# lora_dropout: 0.05
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| 225 |
+
# lora_target_linear: true
|
| 226 |
+
# peft_use_dora: true
|
| 227 |
+
|
| 228 |
+
unfrozen_parameters:
|
| 229 |
+
- ^lm_head.weight$
|
| 230 |
+
- ^model.embed_tokens.weight$
|
| 231 |
+
# mlp.down_proj layers
|
| 232 |
+
- model.layers.1.mlp.down_proj
|
| 233 |
+
- model.layers.35.mlp.down_proj
|
| 234 |
+
- model.layers.38.mlp.down_proj
|
| 235 |
+
- model.layers.37.mlp.down_proj
|
| 236 |
+
- model.layers.36.mlp.down_proj
|
| 237 |
+
- model.layers.15.mlp.down_proj
|
| 238 |
+
- model.layers.11.mlp.down_proj
|
| 239 |
+
- model.layers.12.mlp.down_proj
|
| 240 |
+
- model.layers.34.mlp.down_proj
|
| 241 |
+
- model.layers.44.mlp.down_proj
|
| 242 |
+
- model.layers.45.mlp.down_proj
|
| 243 |
+
- model.layers.9.mlp.down_proj
|
| 244 |
+
- model.layers.41.mlp.down_proj
|
| 245 |
+
- model.layers.33.mlp.down_proj
|
| 246 |
+
- model.layers.43.mlp.down_proj
|
| 247 |
+
- model.layers.40.mlp.down_proj
|
| 248 |
+
- model.layers.13.mlp.down_proj
|
| 249 |
+
- model.layers.8.mlp.down_proj
|
| 250 |
+
- model.layers.39.mlp.down_proj
|
| 251 |
+
- model.layers.10.mlp.down_proj
|
| 252 |
+
- model.layers.14.mlp.down_proj
|
| 253 |
+
- model.layers.16.mlp.down_proj
|
| 254 |
+
- model.layers.31.mlp.down_proj
|
| 255 |
+
- model.layers.32.mlp.down_proj
|
| 256 |
+
# mlp.gate_proj layers
|
| 257 |
+
- model.layers.1.mlp.gate_proj
|
| 258 |
+
- model.layers.44.mlp.gate_proj
|
| 259 |
+
- model.layers.46.mlp.gate_proj
|
| 260 |
+
- model.layers.45.mlp.gate_proj
|
| 261 |
+
- model.layers.43.mlp.gate_proj
|
| 262 |
+
- model.layers.47.mlp.gate_proj
|
| 263 |
+
- model.layers.42.mlp.gate_proj
|
| 264 |
+
- model.layers.32.mlp.gate_proj
|
| 265 |
+
- model.layers.27.mlp.gate_proj
|
| 266 |
+
- model.layers.33.mlp.gate_proj
|
| 267 |
+
- model.layers.28.mlp.gate_proj
|
| 268 |
+
- model.layers.39.mlp.gate_proj
|
| 269 |
+
- model.layers.41.mlp.gate_proj
|
| 270 |
+
- model.layers.40.mlp.gate_proj
|
| 271 |
+
- model.layers.30.mlp.gate_proj
|
| 272 |
+
- model.layers.29.mlp.gate_proj
|
| 273 |
+
- model.layers.31.mlp.gate_proj
|
| 274 |
+
- model.layers.37.mlp.gate_proj
|
| 275 |
+
- model.layers.26.mlp.gate_proj
|
| 276 |
+
- model.layers.10.mlp.gate_proj
|
| 277 |
+
- model.layers.38.mlp.gate_proj
|
| 278 |
+
- model.layers.36.mlp.gate_proj
|
| 279 |
+
- model.layers.12.mlp.gate_proj
|
| 280 |
+
- model.layers.13.mlp.gate_proj
|
| 281 |
+
# mlp.up_proj layers
|
| 282 |
+
- model.layers.1.mlp.up_proj
|
| 283 |
+
- model.layers.13.mlp.up_proj
|
| 284 |
+
- model.layers.11.mlp.up_proj
|
| 285 |
+
- model.layers.14.mlp.up_proj
|
| 286 |
+
- model.layers.15.mlp.up_proj
|
| 287 |
+
- model.layers.12.mlp.up_proj
|
| 288 |
+
- model.layers.8.mlp.up_proj
|
| 289 |
+
- model.layers.16.mlp.up_proj
|
| 290 |
+
- model.layers.9.mlp.up_proj
|
| 291 |
+
- model.layers.19.mlp.up_proj
|
| 292 |
+
- model.layers.10.mlp.up_proj
|
| 293 |
+
- model.layers.7.mlp.up_proj
|
| 294 |
+
- model.layers.17.mlp.up_proj
|
| 295 |
+
- model.layers.20.mlp.up_proj
|
| 296 |
+
- model.layers.21.mlp.up_proj
|
| 297 |
+
- model.layers.18.mlp.up_proj
|
| 298 |
+
- model.layers.37.mlp.up_proj
|
| 299 |
+
- model.layers.38.mlp.up_proj
|
| 300 |
+
- model.layers.39.mlp.up_proj
|
| 301 |
+
- model.layers.42.mlp.up_proj
|
| 302 |
+
- model.layers.41.mlp.up_proj
|
| 303 |
+
- model.layers.27.mlp.up_proj
|
| 304 |
+
- model.layers.28.mlp.up_proj
|
| 305 |
+
- model.layers.36.mlp.up_proj
|
| 306 |
+
# self_attn.k_proj layers
|
| 307 |
+
- model.layers.47.self_attn.k_proj
|
| 308 |
+
- model.layers.39.self_attn.k_proj
|
| 309 |
+
- model.layers.41.self_attn.k_proj
|
| 310 |
+
- model.layers.37.self_attn.k_proj
|
| 311 |
+
- model.layers.35.self_attn.k_proj
|
| 312 |
+
- model.layers.44.self_attn.k_proj
|
| 313 |
+
- model.layers.38.self_attn.k_proj
|
| 314 |
+
- model.layers.14.self_attn.k_proj
|
| 315 |
+
- model.layers.7.self_attn.k_proj
|
| 316 |
+
- model.layers.12.self_attn.k_proj
|
| 317 |
+
- model.layers.11.self_attn.k_proj
|
| 318 |
+
- model.layers.32.self_attn.k_proj
|
| 319 |
+
- model.layers.10.self_attn.k_proj
|
| 320 |
+
- model.layers.8.self_attn.k_proj
|
| 321 |
+
- model.layers.6.self_attn.k_proj
|
| 322 |
+
- model.layers.9.self_attn.k_proj
|
| 323 |
+
- model.layers.45.self_attn.k_proj
|
| 324 |
+
- model.layers.42.self_attn.k_proj
|
| 325 |
+
- model.layers.40.self_attn.k_proj
|
| 326 |
+
- model.layers.5.self_attn.k_proj
|
| 327 |
+
- model.layers.0.self_attn.k_proj
|
| 328 |
+
- model.layers.33.self_attn.k_proj
|
| 329 |
+
- model.layers.34.self_attn.k_proj
|
| 330 |
+
- model.layers.13.self_attn.k_proj
|
| 331 |
+
# self_attn.o_proj layers
|
| 332 |
+
- model.layers.12.self_attn.o_proj
|
| 333 |
+
- model.layers.5.self_attn.o_proj
|
| 334 |
+
- model.layers.14.self_attn.o_proj
|
| 335 |
+
- model.layers.16.self_attn.o_proj
|
| 336 |
+
- model.layers.20.self_attn.o_proj
|
| 337 |
+
- model.layers.13.self_attn.o_proj
|
| 338 |
+
- model.layers.11.self_attn.o_proj
|
| 339 |
+
- model.layers.4.self_attn.o_proj
|
| 340 |
+
- model.layers.6.self_attn.o_proj
|
| 341 |
+
- model.layers.19.self_attn.o_proj
|
| 342 |
+
- model.layers.7.self_attn.o_proj
|
| 343 |
+
- model.layers.18.self_attn.o_proj
|
| 344 |
+
- model.layers.8.self_attn.o_proj
|
| 345 |
+
- model.layers.38.self_attn.o_proj
|
| 346 |
+
- model.layers.15.self_attn.o_proj
|
| 347 |
+
- model.layers.17.self_attn.o_proj
|
| 348 |
+
- model.layers.9.self_attn.o_proj
|
| 349 |
+
- model.layers.10.self_attn.o_proj
|
| 350 |
+
- model.layers.21.self_attn.o_proj
|
| 351 |
+
- model.layers.28.self_attn.o_proj
|
| 352 |
+
- model.layers.32.self_attn.o_proj
|
| 353 |
+
- model.layers.35.self_attn.o_proj
|
| 354 |
+
- model.layers.39.self_attn.o_proj
|
| 355 |
+
- model.layers.3.self_attn.o_proj
|
| 356 |
+
# self_attn.q_proj layers
|
| 357 |
+
- model.layers.1.self_attn.q_proj
|
| 358 |
+
- model.layers.2.self_attn.q_proj
|
| 359 |
+
- model.layers.3.self_attn.q_proj
|
| 360 |
+
- model.layers.44.self_attn.q_proj
|
| 361 |
+
- model.layers.29.self_attn.q_proj
|
| 362 |
+
- model.layers.45.self_attn.q_proj
|
| 363 |
+
- model.layers.43.self_attn.q_proj
|
| 364 |
+
- model.layers.32.self_attn.q_proj
|
| 365 |
+
- model.layers.38.self_attn.q_proj
|
| 366 |
+
- model.layers.19.self_attn.q_proj
|
| 367 |
+
- model.layers.42.self_attn.q_proj
|
| 368 |
+
- model.layers.34.self_attn.q_proj
|
| 369 |
+
- model.layers.36.self_attn.q_proj
|
| 370 |
+
- model.layers.40.self_attn.q_proj
|
| 371 |
+
- model.layers.26.self_attn.q_proj
|
| 372 |
+
- model.layers.20.self_attn.q_proj
|
| 373 |
+
- model.layers.28.self_attn.q_proj
|
| 374 |
+
- model.layers.39.self_attn.q_proj
|
| 375 |
+
- model.layers.41.self_attn.q_proj
|
| 376 |
+
- model.layers.33.self_attn.q_proj
|
| 377 |
+
- model.layers.35.self_attn.q_proj
|
| 378 |
+
- model.layers.25.self_attn.q_proj
|
| 379 |
+
- model.layers.30.self_attn.q_proj
|
| 380 |
+
- model.layers.27.self_attn.q_proj
|
| 381 |
+
# self_attn.v_proj layers
|
| 382 |
+
- model.layers.0.self_attn.v_proj
|
| 383 |
+
- model.layers.7.self_attn.v_proj
|
| 384 |
+
- model.layers.39.self_attn.v_proj
|
| 385 |
+
- model.layers.31.self_attn.v_proj
|
| 386 |
+
- model.layers.15.self_attn.v_proj
|
| 387 |
+
- model.layers.10.self_attn.v_proj
|
| 388 |
+
- model.layers.41.self_attn.v_proj
|
| 389 |
+
- model.layers.32.self_attn.v_proj
|
| 390 |
+
- model.layers.6.self_attn.v_proj
|
| 391 |
+
- model.layers.33.self_attn.v_proj
|
| 392 |
+
- model.layers.42.self_attn.v_proj
|
| 393 |
+
- model.layers.29.self_attn.v_proj
|
| 394 |
+
- model.layers.9.self_attn.v_proj
|
| 395 |
+
- model.layers.14.self_attn.v_proj
|
| 396 |
+
- model.layers.35.self_attn.v_proj
|
| 397 |
+
- model.layers.38.self_attn.v_proj
|
| 398 |
+
- model.layers.13.self_attn.v_proj
|
| 399 |
+
- model.layers.30.self_attn.v_proj
|
| 400 |
+
- model.layers.34.self_attn.v_proj
|
| 401 |
+
- model.layers.5.self_attn.v_proj
|
| 402 |
+
- model.layers.28.self_attn.v_proj
|
| 403 |
+
- model.layers.37.self_attn.v_proj
|
| 404 |
+
- model.layers.27.self_attn.v_proj
|
| 405 |
+
- model.layers.11.self_attn.v_proj
|
| 406 |
+
|
| 407 |
+
wandb_project: EVA-Qwen2.5-14B-SFFT-v0.2
|
| 408 |
+
wandb_entity:
|
| 409 |
+
wandb_watch:
|
| 410 |
+
wandb_name: Unit-02
|
| 411 |
+
wandb_log_model:
|
| 412 |
+
|
| 413 |
+
gradient_accumulation_steps: 8
|
| 414 |
+
micro_batch_size: 2
|
| 415 |
+
num_epochs: 3
|
| 416 |
+
optimizer: paged_ademamix_8bit
|
| 417 |
+
lr_scheduler: cosine
|
| 418 |
+
learning_rate: 0.00005
|
| 419 |
+
max_grad_norm: 3
|
| 420 |
+
|
| 421 |
+
train_on_inputs: false
|
| 422 |
+
group_by_length: false
|
| 423 |
+
bf16: auto
|
| 424 |
+
fp16:
|
| 425 |
+
tf32: false
|
| 426 |
+
|
| 427 |
+
gradient_checkpointing: "unsloth"
|
| 428 |
+
# gradient_checkpointing_kwargs:
|
| 429 |
+
# use_reentrant: true
|
| 430 |
+
early_stopping_patience:
|
| 431 |
+
resume_from_checkpoint:
|
| 432 |
+
local_rank:
|
| 433 |
+
logging_steps: 1
|
| 434 |
+
xformers_attention:
|
| 435 |
+
flash_attention: true
|
| 436 |
+
|
| 437 |
+
warmup_steps: 20
|
| 438 |
+
evals_per_epoch: 4
|
| 439 |
+
saves_per_epoch: 4
|
| 440 |
+
save_safetensors: true
|
| 441 |
+
hub_model_id:
|
| 442 |
+
hub_strategy:
|
| 443 |
+
debug:
|
| 444 |
+
deepspeed: deepspeed_configs/zero3_bf16.json
|
| 445 |
+
weight_decay: 0.1
|
| 446 |
+
# fsdp:
|
| 447 |
+
# - full_shard
|
| 448 |
+
# - auto_wrap
|
| 449 |
+
# fsdp_config:
|
| 450 |
+
# fsdp_limit_all_gathers: true
|
| 451 |
+
# fsdp_sync_module_states: false
|
| 452 |
+
# fsdp_offload_params: true
|
| 453 |
+
# fsdp_cpu_ram_efficient_loading: true
|
| 454 |
+
# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
|
| 455 |
+
# fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
|
| 456 |
+
# fsdp_activation_checkpointing: true
|
| 457 |
+
# fsdp_state_dict_type: SHARDED_STATE_DICT # Changed from FULL_STATE_DICT
|
| 458 |
+
# fsdp_sharding_strategy: FULL_SHARD
|
| 459 |
+
# fsdp_forward_prefetch: false # Added
|
| 460 |
+
# fsdp_backward_prefetch: "BACKWARD_PRE" # Added
|
| 461 |
+
# fsdp_backward_prefetch_limit: 1 # Added
|
| 462 |
+
# fsdp_mixed_precision: BF16 # Added
|
| 463 |
+
|
| 464 |
+
---
|
| 465 |
## Use with llama.cpp
|
| 466 |
Install llama.cpp through brew (works on Mac and Linux)
|
| 467 |
|