Crystalcareai
commited on
Commit
•
e1a9e30
1
Parent(s):
9eeec7b
Create axolotl_config.yml
Browse files- configs/axolotl_config.yml +552 -0
configs/axolotl_config.yml
ADDED
@@ -0,0 +1,552 @@
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1 |
+
base_model: mistralai/Mixtral-8x22B-v0.1
|
2 |
+
model_type: AutoModelForCausalLM
|
3 |
+
tokenizer_type: AutoTokenizer
|
4 |
+
tokenizer_use_fast: true
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5 |
+
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6 |
+
# load_in_8bit: true
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7 |
+
# load_in_4bit: false
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8 |
+
# strict: false
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9 |
+
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10 |
+
datasets:
|
11 |
+
- path: /workspace/datasets/dolphin-2.9.2/dolphin201-sharegpt2.jsonl
|
12 |
+
type: sharegpt
|
13 |
+
conversation: chatml
|
14 |
+
- path: /workspace/datasets/dolphin-2.9.2/dolphin-coder-codegen-sharegpt2.jsonl
|
15 |
+
type: sharegpt
|
16 |
+
conversation: chatml
|
17 |
+
- path: /workspace/datasets/dolphin-2.9.2/dolphin-coder-translate-sharegpt2.jsonl
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18 |
+
type: sharegpt
|
19 |
+
conversation: chatml
|
20 |
+
- path: /workspace/datasets/dolphin-2.9.2/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
|
21 |
+
type: sharegpt
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22 |
+
conversation: chatml
|
23 |
+
- path: /workspace/datasets/dolphin-2.9.2/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
|
24 |
+
type: sharegpt
|
25 |
+
conversation: chatml
|
26 |
+
- path: /workspace/datasets/dolphin-2.9.2/not_samantha_norefusals.jsonl
|
27 |
+
type: sharegpt
|
28 |
+
conversation: chatml
|
29 |
+
- path: /workspace/datasets/dolphin-2.9.2/openhermes200k_unfiltered.jsonl
|
30 |
+
type: sharegpt
|
31 |
+
conversation: chatml
|
32 |
+
- path: /workspace/datasets/dolphin-2.9.2/Orca-Math-resort-unfiltered.jsonl
|
33 |
+
type: sharegpt
|
34 |
+
conversation: chatml
|
35 |
+
- path: /workspace/datasets/dolphin-2.9.2/SystemChat_sharegpt.jsonl
|
36 |
+
type: sharegpt
|
37 |
+
conversation: chatml
|
38 |
+
- path: /workspace/datasets/dolphin-2.9.2/toolbench_instruct_j1s1_3k_unfiltered.jsonl
|
39 |
+
type: sharegpt
|
40 |
+
conversation: chatml
|
41 |
+
- path: /workspace/datasets/dolphin-2.9.2/toolbench_negative_unfiltered.jsonl
|
42 |
+
type: sharegpt
|
43 |
+
conversation: chatml
|
44 |
+
- path: /workspace/datasets/dolphin-2.9.2/toolbench_react_10p_unfiltered.jsonl
|
45 |
+
type: sharegpt
|
46 |
+
conversation: chatml
|
47 |
+
- path: /workspace/datasets/dolphin-2.9.2/toolbench_tflan_cot_30p_unfiltered.jsonl
|
48 |
+
type: sharegpt
|
49 |
+
conversation: chatml
|
50 |
+
- path: /workspace/datasets/dolphin-2.9.2/agent_instruct_react_unfiltered.jsonl
|
51 |
+
type: sharegpt
|
52 |
+
conversation: chatml
|
53 |
+
|
54 |
+
chat_template: chatml
|
55 |
+
dataset_prepared_path: mixtral-8x22b-data
|
56 |
+
val_set_size: 0.01
|
57 |
+
output_dir: mixtral-8x2b
|
58 |
+
|
59 |
+
sequence_len: 16384
|
60 |
+
sample_packing: true
|
61 |
+
pad_to_sequence_len: true
|
62 |
+
|
63 |
+
unfrozen_parameters:
|
64 |
+
- ^lm_head.weight$
|
65 |
+
- ^model.embed_tokens.weight$
|
66 |
+
- model.layers.54.block_sparse_moe.experts.0.w1
|
67 |
+
- model.layers.53.block_sparse_moe.experts.0.w1
|
68 |
+
- model.layers.55.block_sparse_moe.experts.0.w1
|
69 |
+
- model.layers.51.block_sparse_moe.experts.0.w1
|
70 |
+
- model.layers.52.block_sparse_moe.experts.0.w1
|
71 |
+
- model.layers.50.block_sparse_moe.experts.0.w1
|
72 |
+
- model.layers.47.block_sparse_moe.experts.0.w1
|
73 |
+
- model.layers.49.block_sparse_moe.experts.0.w1
|
74 |
+
- model.layers.48.block_sparse_moe.experts.0.w1
|
75 |
+
- model.layers.46.block_sparse_moe.experts.0.w1
|
76 |
+
- model.layers.44.block_sparse_moe.experts.0.w1
|
77 |
+
- model.layers.45.block_sparse_moe.experts.0.w1
|
78 |
+
- model.layers.13.block_sparse_moe.experts.0.w1
|
79 |
+
- model.layers.43.block_sparse_moe.experts.0.w1
|
80 |
+
# block_sparse_moe.experts.0.w2 layers
|
81 |
+
- model.layers.36.block_sparse_moe.experts.0.w2
|
82 |
+
- model.layers.42.block_sparse_moe.experts.0.w2
|
83 |
+
- model.layers.41.block_sparse_moe.experts.0.w2
|
84 |
+
- model.layers.37.block_sparse_moe.experts.0.w2
|
85 |
+
- model.layers.34.block_sparse_moe.experts.0.w2
|
86 |
+
- model.layers.38.block_sparse_moe.experts.0.w2
|
87 |
+
- model.layers.47.block_sparse_moe.experts.0.w2
|
88 |
+
- model.layers.35.block_sparse_moe.experts.0.w2
|
89 |
+
- model.layers.44.block_sparse_moe.experts.0.w2
|
90 |
+
- model.layers.32.block_sparse_moe.experts.0.w2
|
91 |
+
- model.layers.40.block_sparse_moe.experts.0.w2
|
92 |
+
- model.layers.39.block_sparse_moe.experts.0.w2
|
93 |
+
- model.layers.45.block_sparse_moe.experts.0.w2
|
94 |
+
- model.layers.33.block_sparse_moe.experts.0.w2
|
95 |
+
# block_sparse_moe.experts.0.w3 layers
|
96 |
+
- model.layers.46.block_sparse_moe.experts.0.w3
|
97 |
+
- model.layers.47.block_sparse_moe.experts.0.w3
|
98 |
+
- model.layers.44.block_sparse_moe.experts.0.w3
|
99 |
+
- model.layers.45.block_sparse_moe.experts.0.w3
|
100 |
+
- model.layers.43.block_sparse_moe.experts.0.w3
|
101 |
+
- model.layers.49.block_sparse_moe.experts.0.w3
|
102 |
+
- model.layers.48.block_sparse_moe.experts.0.w3
|
103 |
+
- model.layers.42.block_sparse_moe.experts.0.w3
|
104 |
+
- model.layers.36.block_sparse_moe.experts.0.w3
|
105 |
+
- model.layers.39.block_sparse_moe.experts.0.w3
|
106 |
+
- model.layers.41.block_sparse_moe.experts.0.w3
|
107 |
+
- model.layers.38.block_sparse_moe.experts.0.w3
|
108 |
+
- model.layers.50.block_sparse_moe.experts.0.w3
|
109 |
+
- model.layers.37.block_sparse_moe.experts.0.w3
|
110 |
+
# block_sparse_moe.experts.1.w1 layers
|
111 |
+
- model.layers.54.block_sparse_moe.experts.1.w1
|
112 |
+
- model.layers.53.block_sparse_moe.experts.1.w1
|
113 |
+
- model.layers.52.block_sparse_moe.experts.1.w1
|
114 |
+
- model.layers.51.block_sparse_moe.experts.1.w1
|
115 |
+
- model.layers.50.block_sparse_moe.experts.1.w1
|
116 |
+
- model.layers.48.block_sparse_moe.experts.1.w1
|
117 |
+
- model.layers.49.block_sparse_moe.experts.1.w1
|
118 |
+
- model.layers.47.block_sparse_moe.experts.1.w1
|
119 |
+
- model.layers.46.block_sparse_moe.experts.1.w1
|
120 |
+
- model.layers.7.block_sparse_moe.experts.1.w1
|
121 |
+
- model.layers.45.block_sparse_moe.experts.1.w1
|
122 |
+
- model.layers.42.block_sparse_moe.experts.1.w1
|
123 |
+
- model.layers.12.block_sparse_moe.experts.1.w1
|
124 |
+
- model.layers.13.block_sparse_moe.experts.1.w1
|
125 |
+
# block_sparse_moe.experts.1.w2 layers
|
126 |
+
- model.layers.46.block_sparse_moe.experts.1.w2
|
127 |
+
- model.layers.37.block_sparse_moe.experts.1.w2
|
128 |
+
- model.layers.34.block_sparse_moe.experts.1.w2
|
129 |
+
- model.layers.45.block_sparse_moe.experts.1.w2
|
130 |
+
- model.layers.43.block_sparse_moe.experts.1.w2
|
131 |
+
- model.layers.39.block_sparse_moe.experts.1.w2
|
132 |
+
- model.layers.38.block_sparse_moe.experts.1.w2
|
133 |
+
- model.layers.42.block_sparse_moe.experts.1.w2
|
134 |
+
- model.layers.48.block_sparse_moe.experts.1.w2
|
135 |
+
- model.layers.36.block_sparse_moe.experts.1.w2
|
136 |
+
- model.layers.40.block_sparse_moe.experts.1.w2
|
137 |
+
- model.layers.41.block_sparse_moe.experts.1.w2
|
138 |
+
- model.layers.44.block_sparse_moe.experts.1.w2
|
139 |
+
- model.layers.33.block_sparse_moe.experts.1.w2
|
140 |
+
# block_sparse_moe.experts.1.w3 layers
|
141 |
+
- model.layers.47.block_sparse_moe.experts.1.w3
|
142 |
+
- model.layers.46.block_sparse_moe.experts.1.w3
|
143 |
+
- model.layers.48.block_sparse_moe.experts.1.w3
|
144 |
+
- model.layers.42.block_sparse_moe.experts.1.w3
|
145 |
+
- model.layers.45.block_sparse_moe.experts.1.w3
|
146 |
+
- model.layers.40.block_sparse_moe.experts.1.w3
|
147 |
+
- model.layers.43.block_sparse_moe.experts.1.w3
|
148 |
+
- model.layers.38.block_sparse_moe.experts.1.w3
|
149 |
+
- model.layers.39.block_sparse_moe.experts.1.w3
|
150 |
+
- model.layers.41.block_sparse_moe.experts.1.w3
|
151 |
+
- model.layers.34.block_sparse_moe.experts.1.w3
|
152 |
+
- model.layers.37.block_sparse_moe.experts.1.w3
|
153 |
+
- model.layers.44.block_sparse_moe.experts.1.w3
|
154 |
+
- model.layers.49.block_sparse_moe.experts.1.w3
|
155 |
+
# block_sparse_moe.experts.2.w1 layers
|
156 |
+
- model.layers.53.block_sparse_moe.experts.2.w1
|
157 |
+
- model.layers.52.block_sparse_moe.experts.2.w1
|
158 |
+
- model.layers.51.block_sparse_moe.experts.2.w1
|
159 |
+
- model.layers.54.block_sparse_moe.experts.2.w1
|
160 |
+
- model.layers.50.block_sparse_moe.experts.2.w1
|
161 |
+
- model.layers.49.block_sparse_moe.experts.2.w1
|
162 |
+
- model.layers.48.block_sparse_moe.experts.2.w1
|
163 |
+
- model.layers.45.block_sparse_moe.experts.2.w1
|
164 |
+
- model.layers.46.block_sparse_moe.experts.2.w1
|
165 |
+
- model.layers.47.block_sparse_moe.experts.2.w1
|
166 |
+
- model.layers.55.block_sparse_moe.experts.2.w1
|
167 |
+
- model.layers.17.block_sparse_moe.experts.2.w1
|
168 |
+
- model.layers.43.block_sparse_moe.experts.2.w1
|
169 |
+
- model.layers.13.block_sparse_moe.experts.2.w1
|
170 |
+
# block_sparse_moe.experts.2.w2 layers
|
171 |
+
- model.layers.44.block_sparse_moe.experts.2.w2
|
172 |
+
- model.layers.34.block_sparse_moe.experts.2.w2
|
173 |
+
- model.layers.48.block_sparse_moe.experts.2.w2
|
174 |
+
- model.layers.33.block_sparse_moe.experts.2.w2
|
175 |
+
- model.layers.39.block_sparse_moe.experts.2.w2
|
176 |
+
- model.layers.36.block_sparse_moe.experts.2.w2
|
177 |
+
- model.layers.40.block_sparse_moe.experts.2.w2
|
178 |
+
- model.layers.32.block_sparse_moe.experts.2.w2
|
179 |
+
- model.layers.46.block_sparse_moe.experts.2.w2
|
180 |
+
- model.layers.43.block_sparse_moe.experts.2.w2
|
181 |
+
- model.layers.37.block_sparse_moe.experts.2.w2
|
182 |
+
- model.layers.38.block_sparse_moe.experts.2.w2
|
183 |
+
- model.layers.47.block_sparse_moe.experts.2.w2
|
184 |
+
- model.layers.42.block_sparse_moe.experts.2.w2
|
185 |
+
# block_sparse_moe.experts.2.w3 layers
|
186 |
+
- model.layers.46.block_sparse_moe.experts.2.w3
|
187 |
+
- model.layers.48.block_sparse_moe.experts.2.w3
|
188 |
+
- model.layers.45.block_sparse_moe.experts.2.w3
|
189 |
+
- model.layers.47.block_sparse_moe.experts.2.w3
|
190 |
+
- model.layers.43.block_sparse_moe.experts.2.w3
|
191 |
+
- model.layers.49.block_sparse_moe.experts.2.w3
|
192 |
+
- model.layers.40.block_sparse_moe.experts.2.w3
|
193 |
+
- model.layers.44.block_sparse_moe.experts.2.w3
|
194 |
+
- model.layers.39.block_sparse_moe.experts.2.w3
|
195 |
+
- model.layers.38.block_sparse_moe.experts.2.w3
|
196 |
+
- model.layers.41.block_sparse_moe.experts.2.w3
|
197 |
+
- model.layers.52.block_sparse_moe.experts.2.w3
|
198 |
+
- model.layers.51.block_sparse_moe.experts.2.w3
|
199 |
+
- model.layers.50.block_sparse_moe.experts.2.w3
|
200 |
+
# block_sparse_moe.experts.3.w1 layers
|
201 |
+
- model.layers.54.block_sparse_moe.experts.3.w1
|
202 |
+
- model.layers.52.block_sparse_moe.experts.3.w1
|
203 |
+
- model.layers.53.block_sparse_moe.experts.3.w1
|
204 |
+
- model.layers.51.block_sparse_moe.experts.3.w1
|
205 |
+
- model.layers.48.block_sparse_moe.experts.3.w1
|
206 |
+
- model.layers.50.block_sparse_moe.experts.3.w1
|
207 |
+
- model.layers.49.block_sparse_moe.experts.3.w1
|
208 |
+
- model.layers.46.block_sparse_moe.experts.3.w1
|
209 |
+
- model.layers.55.block_sparse_moe.experts.3.w1
|
210 |
+
- model.layers.47.block_sparse_moe.experts.3.w1
|
211 |
+
- model.layers.45.block_sparse_moe.experts.3.w1
|
212 |
+
- model.layers.44.block_sparse_moe.experts.3.w1
|
213 |
+
- model.layers.12.block_sparse_moe.experts.3.w1
|
214 |
+
- model.layers.28.block_sparse_moe.experts.3.w1
|
215 |
+
# block_sparse_moe.experts.3.w2 layers
|
216 |
+
- model.layers.38.block_sparse_moe.experts.3.w2
|
217 |
+
- model.layers.37.block_sparse_moe.experts.3.w2
|
218 |
+
- model.layers.35.block_sparse_moe.experts.3.w2
|
219 |
+
- model.layers.47.block_sparse_moe.experts.3.w2
|
220 |
+
- model.layers.39.block_sparse_moe.experts.3.w2
|
221 |
+
- model.layers.44.block_sparse_moe.experts.3.w2
|
222 |
+
- model.layers.41.block_sparse_moe.experts.3.w2
|
223 |
+
- model.layers.43.block_sparse_moe.experts.3.w2
|
224 |
+
- model.layers.36.block_sparse_moe.experts.3.w2
|
225 |
+
- model.layers.34.block_sparse_moe.experts.3.w2
|
226 |
+
- model.layers.33.block_sparse_moe.experts.3.w2
|
227 |
+
- model.layers.46.block_sparse_moe.experts.3.w2
|
228 |
+
- model.layers.32.block_sparse_moe.experts.3.w2
|
229 |
+
- model.layers.40.block_sparse_moe.experts.3.w2
|
230 |
+
# block_sparse_moe.experts.3.w3 layers
|
231 |
+
- model.layers.46.block_sparse_moe.experts.3.w3
|
232 |
+
- model.layers.48.block_sparse_moe.experts.3.w3
|
233 |
+
- model.layers.45.block_sparse_moe.experts.3.w3
|
234 |
+
- model.layers.47.block_sparse_moe.experts.3.w3
|
235 |
+
- model.layers.44.block_sparse_moe.experts.3.w3
|
236 |
+
- model.layers.43.block_sparse_moe.experts.3.w3
|
237 |
+
- model.layers.49.block_sparse_moe.experts.3.w3
|
238 |
+
- model.layers.41.block_sparse_moe.experts.3.w3
|
239 |
+
- model.layers.39.block_sparse_moe.experts.3.w3
|
240 |
+
- model.layers.36.block_sparse_moe.experts.3.w3
|
241 |
+
- model.layers.37.block_sparse_moe.experts.3.w3
|
242 |
+
- model.layers.50.block_sparse_moe.experts.3.w3
|
243 |
+
- model.layers.35.block_sparse_moe.experts.3.w3
|
244 |
+
- model.layers.42.block_sparse_moe.experts.3.w3
|
245 |
+
# block_sparse_moe.experts.4.w1 layers
|
246 |
+
- model.layers.52.block_sparse_moe.experts.4.w1
|
247 |
+
- model.layers.51.block_sparse_moe.experts.4.w1
|
248 |
+
- model.layers.50.block_sparse_moe.experts.4.w1
|
249 |
+
- model.layers.53.block_sparse_moe.experts.4.w1
|
250 |
+
- model.layers.49.block_sparse_moe.experts.4.w1
|
251 |
+
- model.layers.54.block_sparse_moe.experts.4.w1
|
252 |
+
- model.layers.48.block_sparse_moe.experts.4.w1
|
253 |
+
- model.layers.55.block_sparse_moe.experts.4.w1
|
254 |
+
- model.layers.47.block_sparse_moe.experts.4.w1
|
255 |
+
- model.layers.44.block_sparse_moe.experts.4.w1
|
256 |
+
- model.layers.46.block_sparse_moe.experts.4.w1
|
257 |
+
- model.layers.45.block_sparse_moe.experts.4.w1
|
258 |
+
- model.layers.12.block_sparse_moe.experts.4.w1
|
259 |
+
- model.layers.42.block_sparse_moe.experts.4.w1
|
260 |
+
# block_sparse_moe.experts.4.w2 layers
|
261 |
+
- model.layers.42.block_sparse_moe.experts.4.w2
|
262 |
+
- model.layers.44.block_sparse_moe.experts.4.w2
|
263 |
+
- model.layers.46.block_sparse_moe.experts.4.w2
|
264 |
+
- model.layers.38.block_sparse_moe.experts.4.w2
|
265 |
+
- model.layers.34.block_sparse_moe.experts.4.w2
|
266 |
+
- model.layers.41.block_sparse_moe.experts.4.w2
|
267 |
+
- model.layers.45.block_sparse_moe.experts.4.w2
|
268 |
+
- model.layers.32.block_sparse_moe.experts.4.w2
|
269 |
+
- model.layers.37.block_sparse_moe.experts.4.w2
|
270 |
+
- model.layers.48.block_sparse_moe.experts.4.w2
|
271 |
+
- model.layers.36.block_sparse_moe.experts.4.w2
|
272 |
+
- model.layers.33.block_sparse_moe.experts.4.w2
|
273 |
+
- model.layers.40.block_sparse_moe.experts.4.w2
|
274 |
+
- model.layers.30.block_sparse_moe.experts.4.w2
|
275 |
+
# block_sparse_moe.experts.4.w3 layers
|
276 |
+
- model.layers.48.block_sparse_moe.experts.4.w3
|
277 |
+
- model.layers.44.block_sparse_moe.experts.4.w3
|
278 |
+
- model.layers.47.block_sparse_moe.experts.4.w3
|
279 |
+
- model.layers.46.block_sparse_moe.experts.4.w3
|
280 |
+
- model.layers.45.block_sparse_moe.experts.4.w3
|
281 |
+
- model.layers.49.block_sparse_moe.experts.4.w3
|
282 |
+
- model.layers.38.block_sparse_moe.experts.4.w3
|
283 |
+
- model.layers.40.block_sparse_moe.experts.4.w3
|
284 |
+
- model.layers.43.block_sparse_moe.experts.4.w3
|
285 |
+
- model.layers.36.block_sparse_moe.experts.4.w3
|
286 |
+
- model.layers.42.block_sparse_moe.experts.4.w3
|
287 |
+
- model.layers.41.block_sparse_moe.experts.4.w3
|
288 |
+
- model.layers.50.block_sparse_moe.experts.4.w3
|
289 |
+
- model.layers.37.block_sparse_moe.experts.4.w3
|
290 |
+
# block_sparse_moe.experts.5.w1 layers
|
291 |
+
- model.layers.54.block_sparse_moe.experts.5.w1
|
292 |
+
- model.layers.53.block_sparse_moe.experts.5.w1
|
293 |
+
- model.layers.52.block_sparse_moe.experts.5.w1
|
294 |
+
- model.layers.51.block_sparse_moe.experts.5.w1
|
295 |
+
- model.layers.50.block_sparse_moe.experts.5.w1
|
296 |
+
- model.layers.48.block_sparse_moe.experts.5.w1
|
297 |
+
- model.layers.49.block_sparse_moe.experts.5.w1
|
298 |
+
- model.layers.10.block_sparse_moe.experts.5.w1
|
299 |
+
- model.layers.47.block_sparse_moe.experts.5.w1
|
300 |
+
- model.layers.55.block_sparse_moe.experts.5.w1
|
301 |
+
- model.layers.46.block_sparse_moe.experts.5.w1
|
302 |
+
- model.layers.12.block_sparse_moe.experts.5.w1
|
303 |
+
- model.layers.44.block_sparse_moe.experts.5.w1
|
304 |
+
- model.layers.5.block_sparse_moe.experts.5.w1
|
305 |
+
# block_sparse_moe.experts.5.w2 layers
|
306 |
+
- model.layers.39.block_sparse_moe.experts.5.w2
|
307 |
+
- model.layers.32.block_sparse_moe.experts.5.w2
|
308 |
+
- model.layers.43.block_sparse_moe.experts.5.w2
|
309 |
+
- model.layers.41.block_sparse_moe.experts.5.w2
|
310 |
+
- model.layers.46.block_sparse_moe.experts.5.w2
|
311 |
+
- model.layers.42.block_sparse_moe.experts.5.w2
|
312 |
+
- model.layers.38.block_sparse_moe.experts.5.w2
|
313 |
+
- model.layers.34.block_sparse_moe.experts.5.w2
|
314 |
+
- model.layers.45.block_sparse_moe.experts.5.w2
|
315 |
+
- model.layers.47.block_sparse_moe.experts.5.w2
|
316 |
+
- model.layers.36.block_sparse_moe.experts.5.w2
|
317 |
+
- model.layers.44.block_sparse_moe.experts.5.w2
|
318 |
+
- model.layers.33.block_sparse_moe.experts.5.w2
|
319 |
+
- model.layers.35.block_sparse_moe.experts.5.w2
|
320 |
+
# block_sparse_moe.experts.5.w3 layers
|
321 |
+
- model.layers.48.block_sparse_moe.experts.5.w3
|
322 |
+
- model.layers.46.block_sparse_moe.experts.5.w3
|
323 |
+
- model.layers.47.block_sparse_moe.experts.5.w3
|
324 |
+
- model.layers.44.block_sparse_moe.experts.5.w3
|
325 |
+
- model.layers.38.block_sparse_moe.experts.5.w3
|
326 |
+
- model.layers.41.block_sparse_moe.experts.5.w3
|
327 |
+
- model.layers.49.block_sparse_moe.experts.5.w3
|
328 |
+
- model.layers.42.block_sparse_moe.experts.5.w3
|
329 |
+
- model.layers.40.block_sparse_moe.experts.5.w3
|
330 |
+
- model.layers.43.block_sparse_moe.experts.5.w3
|
331 |
+
- model.layers.36.block_sparse_moe.experts.5.w3
|
332 |
+
- model.layers.39.block_sparse_moe.experts.5.w3
|
333 |
+
- model.layers.45.block_sparse_moe.experts.5.w3
|
334 |
+
- model.layers.37.block_sparse_moe.experts.5.w3
|
335 |
+
# block_sparse_moe.experts.6.w1 layers
|
336 |
+
- model.layers.54.block_sparse_moe.experts.6.w1
|
337 |
+
- model.layers.52.block_sparse_moe.experts.6.w1
|
338 |
+
- model.layers.51.block_sparse_moe.experts.6.w1
|
339 |
+
- model.layers.53.block_sparse_moe.experts.6.w1
|
340 |
+
- model.layers.50.block_sparse_moe.experts.6.w1
|
341 |
+
- model.layers.48.block_sparse_moe.experts.6.w1
|
342 |
+
- model.layers.49.block_sparse_moe.experts.6.w1
|
343 |
+
- model.layers.55.block_sparse_moe.experts.6.w1
|
344 |
+
- model.layers.45.block_sparse_moe.experts.6.w1
|
345 |
+
- model.layers.47.block_sparse_moe.experts.6.w1
|
346 |
+
- model.layers.43.block_sparse_moe.experts.6.w1
|
347 |
+
- model.layers.46.block_sparse_moe.experts.6.w1
|
348 |
+
- model.layers.13.block_sparse_moe.experts.6.w1
|
349 |
+
- model.layers.17.block_sparse_moe.experts.6.w1
|
350 |
+
# block_sparse_moe.experts.6.w2 layers
|
351 |
+
- model.layers.36.block_sparse_moe.experts.6.w2
|
352 |
+
- model.layers.38.block_sparse_moe.experts.6.w2
|
353 |
+
- model.layers.45.block_sparse_moe.experts.6.w2
|
354 |
+
- model.layers.48.block_sparse_moe.experts.6.w2
|
355 |
+
- model.layers.44.block_sparse_moe.experts.6.w2
|
356 |
+
- model.layers.32.block_sparse_moe.experts.6.w2
|
357 |
+
- model.layers.42.block_sparse_moe.experts.6.w2
|
358 |
+
- model.layers.40.block_sparse_moe.experts.6.w2
|
359 |
+
- model.layers.34.block_sparse_moe.experts.6.w2
|
360 |
+
- model.layers.46.block_sparse_moe.experts.6.w2
|
361 |
+
- model.layers.41.block_sparse_moe.experts.6.w2
|
362 |
+
- model.layers.47.block_sparse_moe.experts.6.w2
|
363 |
+
- model.layers.35.block_sparse_moe.experts.6.w2
|
364 |
+
- model.layers.39.block_sparse_moe.experts.6.w2
|
365 |
+
# block_sparse_moe.experts.6.w3 layers
|
366 |
+
- model.layers.46.block_sparse_moe.experts.6.w3
|
367 |
+
- model.layers.45.block_sparse_moe.experts.6.w3
|
368 |
+
- model.layers.43.block_sparse_moe.experts.6.w3
|
369 |
+
- model.layers.48.block_sparse_moe.experts.6.w3
|
370 |
+
- model.layers.47.block_sparse_moe.experts.6.w3
|
371 |
+
- model.layers.37.block_sparse_moe.experts.6.w3
|
372 |
+
- model.layers.44.block_sparse_moe.experts.6.w3
|
373 |
+
- model.layers.40.block_sparse_moe.experts.6.w3
|
374 |
+
- model.layers.41.block_sparse_moe.experts.6.w3
|
375 |
+
- model.layers.36.block_sparse_moe.experts.6.w3
|
376 |
+
- model.layers.42.block_sparse_moe.experts.6.w3
|
377 |
+
- model.layers.38.block_sparse_moe.experts.6.w3
|
378 |
+
- model.layers.39.block_sparse_moe.experts.6.w3
|
379 |
+
- model.layers.35.block_sparse_moe.experts.6.w3
|
380 |
+
# block_sparse_moe.experts.7.w1 layers
|
381 |
+
- model.layers.54.block_sparse_moe.experts.7.w1
|
382 |
+
- model.layers.53.block_sparse_moe.experts.7.w1
|
383 |
+
- model.layers.52.block_sparse_moe.experts.7.w1
|
384 |
+
- model.layers.51.block_sparse_moe.experts.7.w1
|
385 |
+
- model.layers.49.block_sparse_moe.experts.7.w1
|
386 |
+
- model.layers.47.block_sparse_moe.experts.7.w1
|
387 |
+
- model.layers.48.block_sparse_moe.experts.7.w1
|
388 |
+
- model.layers.50.block_sparse_moe.experts.7.w1
|
389 |
+
- model.layers.13.block_sparse_moe.experts.7.w1
|
390 |
+
- model.layers.45.block_sparse_moe.experts.7.w1
|
391 |
+
- model.layers.46.block_sparse_moe.experts.7.w1
|
392 |
+
- model.layers.44.block_sparse_moe.experts.7.w1
|
393 |
+
- model.layers.18.block_sparse_moe.experts.7.w1
|
394 |
+
- model.layers.43.block_sparse_moe.experts.7.w1
|
395 |
+
# block_sparse_moe.experts.7.w2 layers
|
396 |
+
- model.layers.34.block_sparse_moe.experts.7.w2
|
397 |
+
- model.layers.33.block_sparse_moe.experts.7.w2
|
398 |
+
- model.layers.44.block_sparse_moe.experts.7.w2
|
399 |
+
- model.layers.46.block_sparse_moe.experts.7.w2
|
400 |
+
- model.layers.41.block_sparse_moe.experts.7.w2
|
401 |
+
- model.layers.42.block_sparse_moe.experts.7.w2
|
402 |
+
- model.layers.37.block_sparse_moe.experts.7.w2
|
403 |
+
- model.layers.39.block_sparse_moe.experts.7.w2
|
404 |
+
- model.layers.40.block_sparse_moe.experts.7.w2
|
405 |
+
- model.layers.43.block_sparse_moe.experts.7.w2
|
406 |
+
- model.layers.35.block_sparse_moe.experts.7.w2
|
407 |
+
- model.layers.36.block_sparse_moe.experts.7.w2
|
408 |
+
- model.layers.48.block_sparse_moe.experts.7.w2
|
409 |
+
- model.layers.38.block_sparse_moe.experts.7.w2
|
410 |
+
# block_sparse_moe.experts.7.w3 layers
|
411 |
+
- model.layers.47.block_sparse_moe.experts.7.w3
|
412 |
+
- model.layers.46.block_sparse_moe.experts.7.w3
|
413 |
+
- model.layers.45.block_sparse_moe.experts.7.w3
|
414 |
+
- model.layers.44.block_sparse_moe.experts.7.w3
|
415 |
+
- model.layers.40.block_sparse_moe.experts.7.w3
|
416 |
+
- model.layers.48.block_sparse_moe.experts.7.w3
|
417 |
+
- model.layers.43.block_sparse_moe.experts.7.w3
|
418 |
+
- model.layers.41.block_sparse_moe.experts.7.w3
|
419 |
+
- model.layers.39.block_sparse_moe.experts.7.w3
|
420 |
+
- model.layers.42.block_sparse_moe.experts.7.w3
|
421 |
+
- model.layers.49.block_sparse_moe.experts.7.w3
|
422 |
+
- model.layers.31.block_sparse_moe.experts.7.w3
|
423 |
+
- model.layers.37.block_sparse_moe.experts.7.w3
|
424 |
+
- model.layers.35.block_sparse_moe.experts.7.w3
|
425 |
+
# block_sparse_moe.gate layers
|
426 |
+
- model.layers.0.block_sparse_moe.gate
|
427 |
+
- model.layers.1.block_sparse_moe.gate
|
428 |
+
- model.layers.2.block_sparse_moe.gate
|
429 |
+
- model.layers.3.block_sparse_moe.gate
|
430 |
+
- model.layers.4.block_sparse_moe.gate
|
431 |
+
- model.layers.5.block_sparse_moe.gate
|
432 |
+
- model.layers.6.block_sparse_moe.gate
|
433 |
+
- model.layers.7.block_sparse_moe.gate
|
434 |
+
- model.layers.8.block_sparse_moe.gate
|
435 |
+
- model.layers.9.block_sparse_moe.gate
|
436 |
+
- model.layers.10.block_sparse_moe.gate
|
437 |
+
- model.layers.11.block_sparse_moe.gate
|
438 |
+
- model.layers.12.block_sparse_moe.gate
|
439 |
+
- model.layers.13.block_sparse_moe.gate
|
440 |
+
# self_attn.k_proj layers
|
441 |
+
- model.layers.46.self_attn.k_proj
|
442 |
+
- model.layers.48.self_attn.k_proj
|
443 |
+
- model.layers.45.self_attn.k_proj
|
444 |
+
- model.layers.39.self_attn.k_proj
|
445 |
+
- model.layers.44.self_attn.k_proj
|
446 |
+
- model.layers.47.self_attn.k_proj
|
447 |
+
- model.layers.51.self_attn.k_proj
|
448 |
+
- model.layers.36.self_attn.k_proj
|
449 |
+
- model.layers.35.self_attn.k_proj
|
450 |
+
- model.layers.41.self_attn.k_proj
|
451 |
+
- model.layers.42.self_attn.k_proj
|
452 |
+
- model.layers.38.self_attn.k_proj
|
453 |
+
- model.layers.43.self_attn.k_proj
|
454 |
+
- model.layers.34.self_attn.k_proj
|
455 |
+
# self_attn.o_proj layers
|
456 |
+
- model.layers.20.self_attn.o_proj
|
457 |
+
- model.layers.19.self_attn.o_proj
|
458 |
+
- model.layers.16.self_attn.o_proj
|
459 |
+
- model.layers.13.self_attn.o_proj
|
460 |
+
- model.layers.18.self_attn.o_proj
|
461 |
+
- model.layers.17.self_attn.o_proj
|
462 |
+
- model.layers.42.self_attn.o_proj
|
463 |
+
- model.layers.12.self_attn.o_proj
|
464 |
+
- model.layers.14.self_attn.o_proj
|
465 |
+
- model.layers.15.self_attn.o_proj
|
466 |
+
- model.layers.40.self_attn.o_proj
|
467 |
+
- model.layers.22.self_attn.o_proj
|
468 |
+
- model.layers.23.self_attn.o_proj
|
469 |
+
- model.layers.38.self_attn.o_proj
|
470 |
+
# self_attn.q_proj layers
|
471 |
+
- model.layers.0.self_attn.q_proj
|
472 |
+
- model.layers.1.self_attn.q_proj
|
473 |
+
- model.layers.2.self_attn.q_proj
|
474 |
+
- model.layers.22.self_attn.q_proj
|
475 |
+
- model.layers.27.self_attn.q_proj
|
476 |
+
- model.layers.28.self_attn.q_proj
|
477 |
+
- model.layers.13.self_attn.q_proj
|
478 |
+
- model.layers.21.self_attn.q_proj
|
479 |
+
- model.layers.24.self_attn.q_proj
|
480 |
+
- model.layers.33.self_attn.q_proj
|
481 |
+
- model.layers.14.self_attn.q_proj
|
482 |
+
- model.layers.11.self_attn.q_proj
|
483 |
+
- model.layers.15.self_attn.q_proj
|
484 |
+
- model.layers.20.self_attn.q_proj
|
485 |
+
# self_attn.v_proj layers
|
486 |
+
- model.layers.32.self_attn.v_proj
|
487 |
+
- model.layers.34.self_attn.v_proj
|
488 |
+
- model.layers.35.self_attn.v_proj
|
489 |
+
- model.layers.38.self_attn.v_proj
|
490 |
+
- model.layers.41.self_attn.v_proj
|
491 |
+
- model.layers.46.self_attn.v_proj
|
492 |
+
- model.layers.22.self_attn.v_proj
|
493 |
+
- model.layers.29.self_attn.v_proj
|
494 |
+
- model.layers.36.self_attn.v_proj
|
495 |
+
- model.layers.45.self_attn.v_proj
|
496 |
+
- model.layers.31.self_attn.v_proj
|
497 |
+
- model.layers.5.self_attn.v_proj
|
498 |
+
- model.layers.44.self_attn.v_proj
|
499 |
+
- model.layers.8.self_attn.v_proj
|
500 |
+
|
501 |
+
# adapter: lora
|
502 |
+
# lora_model_dir:
|
503 |
+
# lora_r: 32
|
504 |
+
# lora_alpha: 16
|
505 |
+
# lora_dropout: 0.05
|
506 |
+
# lora_target_linear: true
|
507 |
+
# lora_fan_in_fan_out:
|
508 |
+
|
509 |
+
wandb_project: mixtral-8x22b
|
510 |
+
wandb_entity:
|
511 |
+
wandb_watch:
|
512 |
+
wandb_name:
|
513 |
+
wandb_log_model:
|
514 |
+
|
515 |
+
gradient_accumulation_steps: 8
|
516 |
+
micro_batch_size: 1
|
517 |
+
num_epochs: 3
|
518 |
+
optimizer: adamw_8bit
|
519 |
+
lr_scheduler: cosine
|
520 |
+
learning_rate: 1e-5
|
521 |
+
|
522 |
+
train_on_inputs: false
|
523 |
+
group_by_length: false
|
524 |
+
bf16: auto
|
525 |
+
fp16:
|
526 |
+
tf32: false
|
527 |
+
|
528 |
+
gradient_checkpointing: true
|
529 |
+
early_stopping_patience:
|
530 |
+
resume_from_checkpoint:
|
531 |
+
local_rank:
|
532 |
+
logging_steps: 1
|
533 |
+
xformers_attention:
|
534 |
+
flash_attention: true
|
535 |
+
|
536 |
+
warmup_steps: 10
|
537 |
+
evals_per_epoch: 2
|
538 |
+
eval_table_size:
|
539 |
+
eval_max_new_tokens: 128
|
540 |
+
saves_per_epoch: 4
|
541 |
+
save_total_limit: 2
|
542 |
+
debug:
|
543 |
+
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_params.json
|
544 |
+
weight_decay: 0.1
|
545 |
+
fsdp:
|
546 |
+
fsdp_config:
|
547 |
+
special_tokens:
|
548 |
+
eos_token: "<|im_end|>"
|
549 |
+
unk_token: "<unk>"
|
550 |
+
bos_token: "<s>"
|
551 |
+
tokens:
|
552 |
+
- "<|im_start|>"
|