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.gitattributes CHANGED
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+ eva-qwen2.5-32b-v0.0.Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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1
+ ---
2
+ library_name: transformers
3
+ license: apache-2.0
4
+ datasets:
5
+ - anthracite-org/kalo-opus-instruct-22k-no-refusal
6
+ - Nopm/Opus_WritingStruct
7
+ - Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
8
+ - Gryphe/Sonnet3.5-Charcard-Roleplay
9
+ - Gryphe/ChatGPT-4o-Writing-Prompts
10
+ - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
11
+ - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
12
+ - nothingiisreal/Reddit-Dirty-And-WritingPrompts
13
+ - allura-org/Celeste-1.x-data-mixture
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+ base_model: Qwen/Qwen2.5-32B
15
+ tags:
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+ - generated_from_trainer
17
+ model-index:
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+ - name: EVA-Qwen2.5-32B-SFFT-v0.0
19
+ results: []
20
+ ---
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+
22
+ # EVA Qwen2.5-32B v0.0
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+
24
+ <p>
25
+ A RP/storywriting specialist model, full-parameter finetune of Qwen2.5-32B on mixture of synthetic and natural data.<br>
26
+ It uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and "flavor" of the resulting model.<br>
27
+ </p>
28
+
29
+ <p>Model is available for inference on <a href=https://featherless.ai/models/EVA-UNIT-01/EVA-Qwen2.5-32B-v0.0>Featherless.AI</a></p
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+
31
+
32
+ <p>Note: using quantized KV cache with Qwen2.5 <b>is not recommended</b> and can lead to degraded output quality. On the other hand, Qwen's KV cache is already light enough, so using f16 for it shouldn't be problematic.</p>
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+
34
+ <p>
35
+ <p>Prompt format is ChatML.</p><br>
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+ <h3>Recommended sampler values:</h3>
37
+ <ul>
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+ <li>Temperature: 1</li>
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+ <li>Typical-P: 0.9</li>
40
+ <li>Min-P: 0.05</li>
41
+ <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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+
45
+ <h3>Recommended SillyTavern presets (via CalamitousFelicitousness):</h3>
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+
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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)
48
+ - [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)
49
+ </p>
50
+
51
+ <p>
52
+ <br>
53
+ <h3>
54
+ Training data:
55
+ </h3>
56
+ <ul>
57
+ <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>
58
+ <li>Kalomaze's Opus_Instruct_25k dataset, filtered for refusals.</li>
59
+ <li>A subset (1k rows) of ChatGPT-4o-WritingPrompts by Gryphe</li>
60
+ <li>A subset (2k rows) of Sonnet3.5-Charcards-Roleplay by Gryphe</li>
61
+ <li>Synthstruct and SynthRP datasets by Epiculous</li>
62
+ </ul>
63
+ <h3>
64
+ Training time and hardware:
65
+ </h3>
66
+ <ul><li>7 hours on 8xH100 SXM, provided by <a href=https://featherless.ai/>FeatherlessAI</a></li></ul><br>
67
+ </p>
68
+ <p>Model was trained by Kearm and Auri.</p>
69
+ <h4>Special thanks:</h4><ul>
70
+ <li><b>to <a href=https://featherless.ai/>FeatherlessAI</a> for generously providing 8xH100 SXM node for training of this model</b></li>
71
+ <li>to Gryphe, Lemmy, Kalomaze, Nopm and Epiculous for the data</li>
72
+ <li>and to Allura-org for support and feedback on EVA models.</li></ul>
73
+
74
+ [<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)
75
+ <details><summary>See axolotl config</summary>
76
+
77
+ axolotl version: `0.4.1`
78
+ ```yaml
79
+ base_model: Qwen/Qwen2.5-32B
80
+
81
+ load_in_8bit: false
82
+ load_in_4bit: false
83
+ strict: false
84
+
85
+ plugins:
86
+ - axolotl.integrations.liger.LigerPlugin
87
+ liger_rope: true
88
+ liger_rms_norm: true
89
+ liger_swiglu: true
90
+ liger_fused_linear_cross_entropy: true
91
+
92
+ # plugins:
93
+ # - axolotl.integrations.spectrum.SpectrumPlugin
94
+
95
+ # spectrum_top_fraction: 0.5
96
+ # # Optional if using a pre-scanned model as your base_model. Useful if using a model mirror
97
+ # spectrum_model_name: Qwen/Qwen2.5-32B
98
+
99
+ datasets:
100
+ - path: datasets/deduped_Synthstruct-Gens_processed_sharegpt_converted_cleaned.jsonl
101
+ type: sharegpt
102
+ - path: datasets/opus-instruct-22k-no_refusals-filtered.jsonl
103
+ type: sharegpt
104
+ - path: datasets/Celeste_Filtered.jsonl
105
+ type: sharegpt
106
+ - path: datasets/Gryphe-S3-5-Charcards-names-2k.jsonl
107
+ type: sharegpt
108
+ - path: datasets/deduped_SynthRP-Gens_processed_09-25-2024-ShareGPT_converted_cleaned.jsonl
109
+ type: sharegpt
110
+ - path: datasets/deduped_Gryphe-4o-WP-1k.jsonl
111
+ type: sharegpt
112
+ - path: datasets/deduped_not_samantha_norefusals.jsonl
113
+ type: sharegpt
114
+
115
+ chat_template: chatml
116
+ shuffle_merged_datasets: true
117
+ val_set_size: 0.001
118
+ output_dir: ./EVA-Qwen2.5-32B-SFFT-v0.0
119
+
120
+ sequence_len: 8192
121
+ sample_packing: true
122
+ eval_sample_packing: false
123
+ pad_to_sequence_len: true
124
+
125
+ # adapter: qlora
126
+ # lora_model_dir:
127
+ # lora_r: 64
128
+ # lora_alpha: 64
129
+ # lora_dropout: 0.05
130
+ # lora_target_linear: true
131
+ # peft_use_dora: true
132
+
133
+ unfrozen_parameters:
134
+ - ^lm_head.weight$
135
+ - ^model.embed_tokens.weight$
136
+ # input_layernorm layers
137
+ - model.layers.0.input_layernorm
138
+ - model.layers.1.input_layernorm
139
+ - model.layers.2.input_layernorm
140
+ - model.layers.3.input_layernorm
141
+ - model.layers.4.input_layernorm
142
+ - model.layers.5.input_layernorm
143
+ - model.layers.6.input_layernorm
144
+ - model.layers.7.input_layernorm
145
+ - model.layers.8.input_layernorm
146
+ - model.layers.9.input_layernorm
147
+ - model.layers.10.input_layernorm
148
+ - model.layers.11.input_layernorm
149
+ - model.layers.12.input_layernorm
150
+ - model.layers.13.input_layernorm
151
+ - model.layers.14.input_layernorm
152
+ - model.layers.15.input_layernorm
153
+ - model.layers.16.input_layernorm
154
+ - model.layers.17.input_layernorm
155
+ - model.layers.18.input_layernorm
156
+ - model.layers.19.input_layernorm
157
+ - model.layers.20.input_layernorm
158
+ - model.layers.21.input_layernorm
159
+ - model.layers.22.input_layernorm
160
+ - model.layers.23.input_layernorm
161
+ - model.layers.24.input_layernorm
162
+ - model.layers.25.input_layernorm
163
+ - model.layers.26.input_layernorm
164
+ - model.layers.27.input_layernorm
165
+ - model.layers.28.input_layernorm
166
+ - model.layers.29.input_layernorm
167
+ - model.layers.30.input_layernorm
168
+ - model.layers.31.input_layernorm
169
+ # lm_head layers
170
+ # mlp.down_proj layers
171
+ - model.layers.63.mlp.down_proj
172
+ - model.layers.49.mlp.down_proj
173
+ - model.layers.48.mlp.down_proj
174
+ - model.layers.45.mlp.down_proj
175
+ - model.layers.44.mlp.down_proj
176
+ - model.layers.47.mlp.down_proj
177
+ - model.layers.46.mlp.down_proj
178
+ - model.layers.43.mlp.down_proj
179
+ - model.layers.8.mlp.down_proj
180
+ - model.layers.11.mlp.down_proj
181
+ - model.layers.19.mlp.down_proj
182
+ - model.layers.35.mlp.down_proj
183
+ - model.layers.20.mlp.down_proj
184
+ - model.layers.52.mlp.down_proj
185
+ - model.layers.39.mlp.down_proj
186
+ - model.layers.62.mlp.down_proj
187
+ - model.layers.50.mlp.down_proj
188
+ - model.layers.29.mlp.down_proj
189
+ - model.layers.16.mlp.down_proj
190
+ - model.layers.28.mlp.down_proj
191
+ - model.layers.53.mlp.down_proj
192
+ - model.layers.30.mlp.down_proj
193
+ - model.layers.31.mlp.down_proj
194
+ - model.layers.32.mlp.down_proj
195
+ - model.layers.7.mlp.down_proj
196
+ - model.layers.36.mlp.down_proj
197
+ - model.layers.12.mlp.down_proj
198
+ - model.layers.18.mlp.down_proj
199
+ - model.layers.37.mlp.down_proj
200
+ - model.layers.38.mlp.down_proj
201
+ - model.layers.14.mlp.down_proj
202
+ - model.layers.13.mlp.down_proj
203
+ # mlp.gate_proj layers
204
+ - model.layers.43.mlp.gate_proj
205
+ - model.layers.61.mlp.gate_proj
206
+ - model.layers.60.mlp.gate_proj
207
+ - model.layers.44.mlp.gate_proj
208
+ - model.layers.62.mlp.gate_proj
209
+ - model.layers.28.mlp.gate_proj
210
+ - model.layers.29.mlp.gate_proj
211
+ - model.layers.45.mlp.gate_proj
212
+ - model.layers.37.mlp.gate_proj
213
+ - model.layers.35.mlp.gate_proj
214
+ - model.layers.59.mlp.gate_proj
215
+ - model.layers.36.mlp.gate_proj
216
+ - model.layers.30.mlp.gate_proj
217
+ - model.layers.48.mlp.gate_proj
218
+ - model.layers.38.mlp.gate_proj
219
+ - model.layers.27.mlp.gate_proj
220
+ - model.layers.31.mlp.gate_proj
221
+ - model.layers.39.mlp.gate_proj
222
+ - model.layers.34.mlp.gate_proj
223
+ - model.layers.58.mlp.gate_proj
224
+ - model.layers.33.mlp.gate_proj
225
+ - model.layers.26.mlp.gate_proj
226
+ - model.layers.32.mlp.gate_proj
227
+ - model.layers.46.mlp.gate_proj
228
+ - model.layers.42.mlp.gate_proj
229
+ - model.layers.49.mlp.gate_proj
230
+ - model.layers.57.mlp.gate_proj
231
+ - model.layers.50.mlp.gate_proj
232
+ - model.layers.47.mlp.gate_proj
233
+ - model.layers.56.mlp.gate_proj
234
+ - model.layers.63.mlp.gate_proj
235
+ - model.layers.55.mlp.gate_proj
236
+ # mlp.up_proj layers
237
+ - model.layers.61.mlp.up_proj
238
+ - model.layers.60.mlp.up_proj
239
+ - model.layers.32.mlp.up_proj
240
+ - model.layers.59.mlp.up_proj
241
+ - model.layers.58.mlp.up_proj
242
+ - model.layers.57.mlp.up_proj
243
+ - model.layers.44.mlp.up_proj
244
+ - model.layers.28.mlp.up_proj
245
+ - model.layers.35.mlp.up_proj
246
+ - model.layers.36.mlp.up_proj
247
+ - model.layers.31.mlp.up_proj
248
+ - model.layers.34.mlp.up_proj
249
+ - model.layers.55.mlp.up_proj
250
+ - model.layers.29.mlp.up_proj
251
+ - model.layers.49.mlp.up_proj
252
+ - model.layers.30.mlp.up_proj
253
+ - model.layers.53.mlp.up_proj
254
+ - model.layers.43.mlp.up_proj
255
+ - model.layers.56.mlp.up_proj
256
+ - model.layers.33.mlp.up_proj
257
+ - model.layers.54.mlp.up_proj
258
+ - model.layers.62.mlp.up_proj
259
+ - model.layers.27.mlp.up_proj
260
+ - model.layers.51.mlp.up_proj
261
+ - model.layers.52.mlp.up_proj
262
+ - model.layers.37.mlp.up_proj
263
+ - model.layers.45.mlp.up_proj
264
+ - model.layers.26.mlp.up_proj
265
+ - model.layers.42.mlp.up_proj
266
+ - model.layers.50.mlp.up_proj
267
+ - model.layers.48.mlp.up_proj
268
+ - model.layers.39.mlp.up_proj
269
+ # model.embed_tokens layers
270
+ # model.norm layers
271
+ # post_attention_layernorm layers
272
+ - model.layers.0.post_attention_layernorm
273
+ - model.layers.1.post_attention_layernorm
274
+ - model.layers.2.post_attention_layernorm
275
+ - model.layers.3.post_attention_layernorm
276
+ - model.layers.4.post_attention_layernorm
277
+ - model.layers.5.post_attention_layernorm
278
+ - model.layers.6.post_attention_layernorm
279
+ - model.layers.7.post_attention_layernorm
280
+ - model.layers.8.post_attention_layernorm
281
+ - model.layers.9.post_attention_layernorm
282
+ - model.layers.10.post_attention_layernorm
283
+ - model.layers.11.post_attention_layernorm
284
+ - model.layers.12.post_attention_layernorm
285
+ - model.layers.13.post_attention_layernorm
286
+ - model.layers.14.post_attention_layernorm
287
+ - model.layers.15.post_attention_layernorm
288
+ - model.layers.16.post_attention_layernorm
289
+ - model.layers.17.post_attention_layernorm
290
+ - model.layers.18.post_attention_layernorm
291
+ - model.layers.19.post_attention_layernorm
292
+ - model.layers.20.post_attention_layernorm
293
+ - model.layers.21.post_attention_layernorm
294
+ - model.layers.22.post_attention_layernorm
295
+ - model.layers.23.post_attention_layernorm
296
+ - model.layers.24.post_attention_layernorm
297
+ - model.layers.25.post_attention_layernorm
298
+ - model.layers.26.post_attention_layernorm
299
+ - model.layers.27.post_attention_layernorm
300
+ - model.layers.28.post_attention_layernorm
301
+ - model.layers.29.post_attention_layernorm
302
+ - model.layers.30.post_attention_layernorm
303
+ - model.layers.31.post_attention_layernorm
304
+ # self_attn.k_proj layers
305
+ - model.layers.63.self_attn.k_proj
306
+ - model.layers.55.self_attn.k_proj
307
+ - model.layers.60.self_attn.k_proj
308
+ - model.layers.7.self_attn.k_proj
309
+ - model.layers.12.self_attn.k_proj
310
+ - model.layers.13.self_attn.k_proj
311
+ - model.layers.57.self_attn.k_proj
312
+ - model.layers.29.self_attn.k_proj
313
+ - model.layers.14.self_attn.k_proj
314
+ - model.layers.51.self_attn.k_proj
315
+ - model.layers.53.self_attn.k_proj
316
+ - model.layers.54.self_attn.k_proj
317
+ - model.layers.22.self_attn.k_proj
318
+ - model.layers.61.self_attn.k_proj
319
+ - model.layers.18.self_attn.k_proj
320
+ - model.layers.30.self_attn.k_proj
321
+ - model.layers.9.self_attn.k_proj
322
+ - model.layers.24.self_attn.k_proj
323
+ - model.layers.23.self_attn.k_proj
324
+ - model.layers.25.self_attn.k_proj
325
+ - model.layers.10.self_attn.k_proj
326
+ - model.layers.58.self_attn.k_proj
327
+ - model.layers.56.self_attn.k_proj
328
+ - model.layers.15.self_attn.k_proj
329
+ - model.layers.32.self_attn.k_proj
330
+ - model.layers.28.self_attn.k_proj
331
+ - model.layers.8.self_attn.k_proj
332
+ - model.layers.59.self_attn.k_proj
333
+ - model.layers.11.self_attn.k_proj
334
+ - model.layers.48.self_attn.k_proj
335
+ - model.layers.16.self_attn.k_proj
336
+ - model.layers.50.self_attn.k_proj
337
+ # self_attn.o_proj layers
338
+ - model.layers.15.self_attn.o_proj
339
+ - model.layers.23.self_attn.o_proj
340
+ - model.layers.31.self_attn.o_proj
341
+ - model.layers.30.self_attn.o_proj
342
+ - model.layers.18.self_attn.o_proj
343
+ - model.layers.24.self_attn.o_proj
344
+ - model.layers.17.self_attn.o_proj
345
+ - model.layers.28.self_attn.o_proj
346
+ - model.layers.34.self_attn.o_proj
347
+ - model.layers.33.self_attn.o_proj
348
+ - model.layers.25.self_attn.o_proj
349
+ - model.layers.12.self_attn.o_proj
350
+ - model.layers.14.self_attn.o_proj
351
+ - model.layers.29.self_attn.o_proj
352
+ - model.layers.16.self_attn.o_proj
353
+ - model.layers.26.self_attn.o_proj
354
+ - model.layers.22.self_attn.o_proj
355
+ - model.layers.27.self_attn.o_proj
356
+ - model.layers.35.self_attn.o_proj
357
+ - model.layers.20.self_attn.o_proj
358
+ - model.layers.13.self_attn.o_proj
359
+ - model.layers.36.self_attn.o_proj
360
+ - model.layers.19.self_attn.o_proj
361
+ - model.layers.37.self_attn.o_proj
362
+ - model.layers.21.self_attn.o_proj
363
+ - model.layers.11.self_attn.o_proj
364
+ - model.layers.54.self_attn.o_proj
365
+ - model.layers.5.self_attn.o_proj
366
+ - model.layers.38.self_attn.o_proj
367
+ - model.layers.6.self_attn.o_proj
368
+ - model.layers.8.self_attn.o_proj
369
+ - model.layers.9.self_attn.o_proj
370
+ # self_attn.q_proj layers
371
+ - model.layers.1.self_attn.q_proj
372
+ - model.layers.2.self_attn.q_proj
373
+ - model.layers.3.self_attn.q_proj
374
+ - model.layers.45.self_attn.q_proj
375
+ - model.layers.54.self_attn.q_proj
376
+ - model.layers.35.self_attn.q_proj
377
+ - model.layers.48.self_attn.q_proj
378
+ - model.layers.61.self_attn.q_proj
379
+ - model.layers.52.self_attn.q_proj
380
+ - model.layers.50.self_attn.q_proj
381
+ - model.layers.60.self_attn.q_proj
382
+ - model.layers.56.self_attn.q_proj
383
+ - model.layers.58.self_attn.q_proj
384
+ - model.layers.42.self_attn.q_proj
385
+ - model.layers.59.self_attn.q_proj
386
+ - model.layers.44.self_attn.q_proj
387
+ - model.layers.55.self_attn.q_proj
388
+ - model.layers.57.self_attn.q_proj
389
+ - model.layers.41.self_attn.q_proj
390
+ - model.layers.36.self_attn.q_proj
391
+ - model.layers.39.self_attn.q_proj
392
+ - model.layers.4.self_attn.q_proj
393
+ - model.layers.43.self_attn.q_proj
394
+ - model.layers.34.self_attn.q_proj
395
+ - model.layers.46.self_attn.q_proj
396
+ - model.layers.49.self_attn.q_proj
397
+ - model.layers.40.self_attn.q_proj
398
+ - model.layers.25.self_attn.q_proj
399
+ - model.layers.51.self_attn.q_proj
400
+ - model.layers.17.self_attn.q_proj
401
+ - model.layers.37.self_attn.q_proj
402
+ - model.layers.53.self_attn.q_proj
403
+ # self_attn.v_proj layers
404
+ - model.layers.55.self_attn.v_proj
405
+ - model.layers.31.self_attn.v_proj
406
+ - model.layers.47.self_attn.v_proj
407
+ - model.layers.45.self_attn.v_proj
408
+ - model.layers.49.self_attn.v_proj
409
+ - model.layers.48.self_attn.v_proj
410
+ - model.layers.15.self_attn.v_proj
411
+ - model.layers.30.self_attn.v_proj
412
+ - model.layers.7.self_attn.v_proj
413
+ - model.layers.44.self_attn.v_proj
414
+ - model.layers.29.self_attn.v_proj
415
+ - model.layers.51.self_attn.v_proj
416
+ - model.layers.50.self_attn.v_proj
417
+ - model.layers.14.self_attn.v_proj
418
+ - model.layers.54.self_attn.v_proj
419
+ - model.layers.32.self_attn.v_proj
420
+ - model.layers.43.self_attn.v_proj
421
+ - model.layers.10.self_attn.v_proj
422
+ - model.layers.46.self_attn.v_proj
423
+ - model.layers.38.self_attn.v_proj
424
+ - model.layers.57.self_attn.v_proj
425
+ - model.layers.22.self_attn.v_proj
426
+ - model.layers.39.self_attn.v_proj
427
+ - model.layers.6.self_attn.v_proj
428
+ - model.layers.23.self_attn.v_proj
429
+ - model.layers.58.self_attn.v_proj
430
+ - model.layers.53.self_attn.v_proj
431
+ - model.layers.40.self_attn.v_proj
432
+ - model.layers.24.self_attn.v_proj
433
+ - model.layers.9.self_attn.v_proj
434
+ - model.layers.25.self_attn.v_proj
435
+ - model.layers.5.self_attn.v_proj
436
+
437
+
438
+ wandb_project: EVA-Qwen2.5-32B-SFFT-v0.0
439
+ wandb_entity:
440
+ wandb_watch:
441
+ wandb_name: Unit-00
442
+ wandb_log_model:
443
+
444
+ gradient_accumulation_steps: 8
445
+ micro_batch_size: 1
446
+ num_epochs: 3
447
+ optimizer: paged_adamw_8bit
448
+ lr_scheduler: cosine
449
+ learning_rate: 0.00003
450
+ max_grad_norm: 3
451
+
452
+ train_on_inputs: false
453
+ group_by_length: false
454
+ bf16: auto
455
+ fp16:
456
+ tf32: true
457
+
458
+ gradient_checkpointing: "unsloth"
459
+ # gradient_checkpointing_kwargs:
460
+ # use_reentrant: true
461
+ early_stopping_patience:
462
+ resume_from_checkpoint:
463
+ local_rank:
464
+ logging_steps: 1
465
+ xformers_attention:
466
+ flash_attention: true
467
+
468
+ warmup_steps: 20
469
+ evals_per_epoch: 4
470
+ saves_per_epoch: 2
471
+ save_safetensors: true
472
+ hub_model_id:
473
+ hub_strategy:
474
+ debug:
475
+ deepspeed: deepspeed_configs/zero3_bf16.json
476
+ weight_decay: 0.1
477
+ # fsdp:
478
+ # - full_shard
479
+ # - auto_wrap
480
+ # fsdp_config:
481
+ # fsdp_limit_all_gathers: true
482
+ # fsdp_sync_module_states: true
483
+ # fsdp_offload_params: false # Changed from true
484
+ # fsdp_use_orig_params: true # Changed from false
485
+ # fsdp_cpu_ram_efficient_loading: true
486
+ # fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
487
+ # fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
488
+ # fsdp_activation_checkpointing: true
489
+ # fsdp_state_dict_type: SHARDED_STATE_DICT # Changed from FULL_STATE_DICT
490
+ # fsdp_sharding_strategy: FULL_SHARD
491
+ # fsdp_forward_prefetch: true # Added
492
+ # fsdp_backward_prefetch: "BACKWARD_POST" # Added
493
+ # fsdp_backward_prefetch_limit: 1 # Added
494
+ # fsdp_mixed_precision: BF16 # Added
495
+ ```
496
+
497
+ </details><br>
eva-qwen2.5-32b-v0.0.Q4_0.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ size 18640229088