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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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+ 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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+
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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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+
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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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+
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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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+
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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/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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+
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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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+
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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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+
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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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+ 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
121
+ - 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
133
+ - model.layers.39.mlp.gate_proj
134
+ - model.layers.26.mlp.gate_proj
135
+ - model.layers.32.mlp.gate_proj
136
+ - model.layers.46.mlp.gate_proj
137
+ - model.layers.42.mlp.gate_proj
138
+ - model.layers.49.mlp.gate_proj
139
+ - model.layers.57.mlp.gate_proj
140
+ - model.layers.50.mlp.gate_proj
141
+ - model.layers.47.mlp.gate_proj
142
+ - model.layers.56.mlp.gate_proj
143
+ - model.layers.63.mlp.gate_proj
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+ - model.layers.55.mlp.gate_proj
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+ # mlp.up_proj layers
146
+ - model.layers.61.mlp.up_proj
147
+ - model.layers.60.mlp.up_proj
148
+ - model.layers.32.mlp.up_proj
149
+ - model.layers.59.mlp.up_proj
150
+ - model.layers.58.mlp.up_proj
151
+ - model.layers.57.mlp.up_proj
152
+ - model.layers.44.mlp.up_proj
153
+ - model.layers.28.mlp.up_proj
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+ - model.layers.35.mlp.up_proj
155
+ - model.layers.36.mlp.up_proj
156
+ - model.layers.29.mlp.up_proj
157
+ - model.layers.31.mlp.up_proj
158
+ - model.layers.34.mlp.up_proj
159
+ - model.layers.55.mlp.up_proj
160
+ - model.layers.49.mlp.up_proj
161
+ - model.layers.30.mlp.up_proj
162
+ - model.layers.53.mlp.up_proj
163
+ - model.layers.43.mlp.up_proj
164
+ - model.layers.56.mlp.up_proj
165
+ - 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
168
+ - 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
171
+ - model.layers.37.mlp.up_proj
172
+ - model.layers.45.mlp.up_proj
173
+ - 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
177
+ - model.layers.39.mlp.up_proj
178
+ # self_attn.k_proj layers
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+ - model.layers.63.self_attn.k_proj
180
+ - model.layers.55.self_attn.k_proj
181
+ - model.layers.60.self_attn.k_proj
182
+ - model.layers.7.self_attn.k_proj
183
+ - model.layers.12.self_attn.k_proj
184
+ - model.layers.13.self_attn.k_proj
185
+ - model.layers.57.self_attn.k_proj
186
+ - model.layers.29.self_attn.k_proj
187
+ - model.layers.14.self_attn.k_proj
188
+ - model.layers.51.self_attn.k_proj
189
+ - model.layers.53.self_attn.k_proj
190
+ - model.layers.54.self_attn.k_proj
191
+ - model.layers.22.self_attn.k_proj
192
+ - model.layers.61.self_attn.k_proj
193
+ - model.layers.18.self_attn.k_proj
194
+ - model.layers.30.self_attn.k_proj
195
+ - model.layers.9.self_attn.k_proj
196
+ - model.layers.24.self_attn.k_proj
197
+ - model.layers.23.self_attn.k_proj
198
+ - model.layers.25.self_attn.k_proj
199
+ - model.layers.10.self_attn.k_proj
200
+ - model.layers.58.self_attn.k_proj
201
+ - model.layers.56.self_attn.k_proj
202
+ - model.layers.15.self_attn.k_proj
203
+ - model.layers.32.self_attn.k_proj
204
+ - model.layers.28.self_attn.k_proj
205
+ - model.layers.8.self_attn.k_proj
206
+ - model.layers.59.self_attn.k_proj
207
+ - model.layers.11.self_attn.k_proj
208
+ - model.layers.48.self_attn.k_proj
209
+ - model.layers.16.self_attn.k_proj
210
+ - model.layers.50.self_attn.k_proj
211
+ # self_attn.o_proj layers
212
+ - model.layers.15.self_attn.o_proj
213
+ - model.layers.23.self_attn.o_proj
214
+ - model.layers.31.self_attn.o_proj
215
+ - model.layers.30.self_attn.o_proj
216
+ - model.layers.18.self_attn.o_proj
217
+ - model.layers.24.self_attn.o_proj
218
+ - model.layers.17.self_attn.o_proj
219
+ - model.layers.28.self_attn.o_proj
220
+ - model.layers.34.self_attn.o_proj
221
+ - model.layers.33.self_attn.o_proj
222
+ - model.layers.25.self_attn.o_proj
223
+ - model.layers.12.self_attn.o_proj
224
+ - model.layers.14.self_attn.o_proj
225
+ - model.layers.29.self_attn.o_proj
226
+ - model.layers.16.self_attn.o_proj
227
+ - model.layers.26.self_attn.o_proj
228
+ - model.layers.22.self_attn.o_proj
229
+ - model.layers.27.self_attn.o_proj
230
+ - model.layers.35.self_attn.o_proj
231
+ - model.layers.20.self_attn.o_proj
232
+ - model.layers.13.self_attn.o_proj
233
+ - model.layers.36.self_attn.o_proj
234
+ - model.layers.19.self_attn.o_proj
235
+ - model.layers.37.self_attn.o_proj
236
+ - model.layers.21.self_attn.o_proj
237
+ - model.layers.11.self_attn.o_proj
238
+ - model.layers.54.self_attn.o_proj
239
+ - model.layers.5.self_attn.o_proj
240
+ - model.layers.38.self_attn.o_proj
241
+ - model.layers.6.self_attn.o_proj
242
+ - model.layers.8.self_attn.o_proj
243
+ - model.layers.9.self_attn.o_proj
244
+ # self_attn.q_proj layers
245
+ - model.layers.1.self_attn.q_proj
246
+ - model.layers.2.self_attn.q_proj
247
+ - model.layers.3.self_attn.q_proj
248
+ - model.layers.45.self_attn.q_proj
249
+ - model.layers.54.self_attn.q_proj
250
+ - model.layers.35.self_attn.q_proj
251
+ - model.layers.48.self_attn.q_proj
252
+ - model.layers.61.self_attn.q_proj
253
+ - model.layers.52.self_attn.q_proj
254
+ - model.layers.50.self_attn.q_proj
255
+ - model.layers.60.self_attn.q_proj
256
+ - model.layers.56.self_attn.q_proj
257
+ - model.layers.58.self_attn.q_proj
258
+ - model.layers.42.self_attn.q_proj
259
+ - model.layers.59.self_attn.q_proj
260
+ - model.layers.44.self_attn.q_proj
261
+ - model.layers.55.self_attn.q_proj
262
+ - model.layers.57.self_attn.q_proj
263
+ - model.layers.41.self_attn.q_proj
264
+ - model.layers.36.self_attn.q_proj
265
+ - model.layers.39.self_attn.q_proj
266
+ - model.layers.4.self_attn.q_proj
267
+ - model.layers.43.self_attn.q_proj
268
+ - model.layers.34.self_attn.q_proj
269
+ - model.layers.46.self_attn.q_proj
270
+ - model.layers.49.self_attn.q_proj
271
+ - model.layers.40.self_attn.q_proj
272
+ - model.layers.25.self_attn.q_proj
273
+ - model.layers.51.self_attn.q_proj
274
+ - model.layers.17.self_attn.q_proj
275
+ - model.layers.37.self_attn.q_proj
276
+ - model.layers.53.self_attn.q_proj
277
+ # self_attn.v_proj layers
278
+ - model.layers.55.self_attn.v_proj
279
+ - model.layers.31.self_attn.v_proj
280
+ - model.layers.47.self_attn.v_proj
281
+ - model.layers.45.self_attn.v_proj
282
+ - model.layers.49.self_attn.v_proj
283
+ - model.layers.48.self_attn.v_proj
284
+ - model.layers.15.self_attn.v_proj
285
+ - model.layers.30.self_attn.v_proj
286
+ - model.layers.7.self_attn.v_proj
287
+ - model.layers.44.self_attn.v_proj
288
+ - model.layers.29.self_attn.v_proj
289
+ - model.layers.51.self_attn.v_proj
290
+ - model.layers.50.self_attn.v_proj
291
+ - model.layers.14.self_attn.v_proj
292
+ - model.layers.54.self_attn.v_proj
293
+ - model.layers.32.self_attn.v_proj
294
+ - model.layers.43.self_attn.v_proj
295
+ - model.layers.10.self_attn.v_proj
296
+ - model.layers.46.self_attn.v_proj
297
+ - model.layers.38.self_attn.v_proj
298
+ - model.layers.57.self_attn.v_proj
299
+ - model.layers.22.self_attn.v_proj
300
+ - model.layers.39.self_attn.v_proj
301
+ - model.layers.6.self_attn.v_proj
302
+ - model.layers.23.self_attn.v_proj
303
+ - model.layers.58.self_attn.v_proj
304
+ - model.layers.53.self_attn.v_proj
305
+ - model.layers.40.self_attn.v_proj
306
+ - model.layers.24.self_attn.v_proj
307
+ - model.layers.9.self_attn.v_proj
308
+ - model.layers.25.self_attn.v_proj
309
+ - model.layers.5.self_attn.v_proj
310
+
311
+
312
+
313
+ wandb_project: EVA-Qwen2.5-32B-SFFT-v0.1
314
+ wandb_entity:
315
+ wandb_watch:
316
+ wandb_name: Unit-01
317
+ wandb_log_model:
318
+
319
+ gradient_accumulation_steps: 8
320
+ micro_batch_size: 1
321
+ num_epochs: 3
322
+ optimizer: paged_adamw_8bit
323
+ lr_scheduler: cosine
324
+ learning_rate: 0.00005
325
+ max_grad_norm: 3
326
+
327
+ train_on_inputs: false
328
+ group_by_length: false
329
+ bf16: auto
330
+ fp16:
331
+ tf32: false
332
+
333
+ gradient_checkpointing: "unsloth"
334
+ # gradient_checkpointing_kwargs:
335
+ # use_reentrant: true
336
+ early_stopping_patience:
337
+ resume_from_checkpoint:
338
+ local_rank:
339
+ logging_steps: 1
340
+ xformers_attention:
341
+ flash_attention: true
342
+
343
+ warmup_steps: 20
344
+ evals_per_epoch: 4
345
+ saves_per_epoch: 2
346
+ save_safetensors: true
347
+ hub_model_id:
348
+ hub_strategy:
349
+ debug:
350
+ deepspeed: deepspeed_configs/zero3_bf16.json
351
+ weight_decay: 0.1
352
+ # fsdp:
353
+ # - full_shard
354
+ # - auto_wrap
355
+ # fsdp_config:
356
+ # fsdp_limit_all_gathers: true
357
+ # fsdp_sync_module_states: false
358
+ # fsdp_offload_params: true
359
+ # fsdp_cpu_ram_efficient_loading: true
360
+ # fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
361
+ # fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
362
+ # fsdp_activation_checkpointing: true
363
+ # fsdp_state_dict_type: SHARDED_STATE_DICT # Changed from FULL_STATE_DICT
364
+ # fsdp_sharding_strategy: FULL_SHARD
365
+ # fsdp_forward_prefetch: false # Added
366
+ # fsdp_backward_prefetch: "BACKWARD_PRE" # Added
367
+ # fsdp_backward_prefetch_limit: 1 # Added
368
+ # fsdp_mixed_precision: BF16 # Added
369
+ ```
370
+
371
+ </details><br>
372
+
373
+ # EVA-Qwen2.5-32B-SFFT-v0.1
374
+
375
+ This model is a fine-tuned version of [Qwen/Qwen2.5-32B](https://huggingface.co/Qwen/Qwen2.5-32B) on the None dataset.
376
+ It achieves the following results on the evaluation set:
377
+ - Loss: 1.0347
378
+
379
+ ## Model description
380
+
381
+ More information needed
382
+
383
+ ## Intended uses & limitations
384
+
385
+ More information needed
386
+
387
+ ## Training and evaluation data
388
+
389
+ More information needed
390
+
391
+ ## Training procedure
392
+
393
+ ### Training hyperparameters
394
+
395
+ The following hyperparameters were used during training:
396
+ - learning_rate: 5e-05
397
+ - train_batch_size: 1
398
+ - eval_batch_size: 1
399
+ - seed: 42
400
+ - distributed_type: multi-GPU
401
+ - num_devices: 8
402
+ - gradient_accumulation_steps: 8
403
+ - total_train_batch_size: 64
404
+ - total_eval_batch_size: 8
405
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
406
+ - lr_scheduler_type: cosine
407
+ - lr_scheduler_warmup_steps: 20
408
+ - num_epochs: 3
409
+
410
+ ### Training results
411
+
412
+ | Training Loss | Epoch | Step | Validation Loss |
413
+ |:-------------:|:------:|:----:|:---------------:|
414
+ | 1.4186 | 0.0068 | 1 | 1.4219 |
415
+ | 1.1535 | 0.2532 | 37 | 1.0748 |
416
+ | 1.0027 | 0.5064 | 74 | 1.0227 |
417
+ | 0.9742 | 0.7596 | 111 | 1.0011 |
418
+ | 0.7284 | 1.0120 | 148 | 1.0106 |
419
+ | 0.6779 | 1.2666 | 185 | 1.0126 |
420
+ | 0.6424 | 1.5211 | 222 | 1.0009 |
421
+ | 0.6818 | 1.7756 | 259 | 0.9927 |
422
+ | 0.4779 | 2.0233 | 296 | 1.0260 |
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+ | 0.4423 | 2.2782 | 333 | 1.0372 |
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+ | 0.4613 | 2.5332 | 370 | 1.0365 |
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+ | 0.4332 | 2.7881 | 407 | 1.0347 |
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