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Duplicate from cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b

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Co-authored-by: Eric Hartford <ehartford@users.noreply.huggingface.co>

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+ ---
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+ license: apache-2.0
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+ base_model: mistralai/Mistral-Nemo-Base-2407
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+ tags:
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+ - generated_from_trainer
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+ - axolotl
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+ datasets:
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+ - cognitivecomputations/Dolphin-2.9
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+ - teknium/OpenHermes-2.5
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+ - m-a-p/CodeFeedback-Filtered-Instruction
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+ - cognitivecomputations/dolphin-coder
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+ - cognitivecomputations/samantha-data
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+ - microsoft/orca-math-word-problems-200k
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+ - Locutusque/function-calling-chatml
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+ - internlm/Agent-FLAN
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+ ---
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+
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+ # Dolphin 2.9.3 Mistral Nemo 12b 🐬
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+
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+ Curated and trained by Eric Hartford and Cognitive Computations
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+
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+ [![Discord](https://img.shields.io/discord/1156064224225808488?logo=Discord&logoColor=%23ffffff&label=Discord&link=https%3A%2F%2Fdiscord.gg%2FtCMkMDDHwm)](https://discord.gg/h3K4XGj2RH)
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+ Discord: https://discord.gg/h3K4XGj2RH
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+
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" />
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+
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+ Our appreciation for the sponsors of Dolphin 2.9.3:
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+ - [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xL40S node
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+
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+ This model is based on mistralai/Mistral-Nemo-Base-2407, and is governed by the apache 2.0 license.
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+
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+ The base model has 128K context, and our finetuning used 8192 sequence length.
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+
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+ Dolphin 2.9.3 uses ChatML prompt template format.
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+
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+ example:
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+
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+ ```
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+ <|im_start|>system
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+ You are Dolphin, a helpful AI assistant.<|im_end|>
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+ <|im_start|>user
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+ {prompt}<|im_end|>
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+ <|im_start|>assistant
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+
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+ ```
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+
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+ Dolphin-2.9.3 has a variety of instruction following, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
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+
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+ Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
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+
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+ Dolphin is licensed according to apache 2.0 license. We grant permission for any use, including commercial. Dolphin was trained on data generated from GPT4, among other models.
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+
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+ ## Evals
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+
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+ TBD
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+
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+ ## Training
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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: /workspace/models/Mistral-Nemo-Base-2407
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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+ load_in_8bit: false
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+ # load_in_4bit: true
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+ strict: false
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+
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+ datasets:
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+ - path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/SystemChat_filtered_sharegpt.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/SystemChat_multilingual_sharegpt.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-translate-sharegpt2.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-codegen-sharegpt2.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/not_samantha_norefusals.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/Orca-Math-resort-unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/agent_instruct_react_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/toolbench_instruct_j1s1_3k_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/toolbench_negative_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/toolbench_react_10p_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/toolbench_tflan_cot_30p_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+ - path: /workspace/datasets/dolphin-2.9.3/openhermes200k_unfiltered.jsonl
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+ type: sharegpt
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+ conversation: chatml
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+
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+ chat_template: chatml
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+ # adapter: qlora
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+ # lora_r: 128
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+ # lora_alpha: 16
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+ # lora_modules_to_save: [embed_tokens, lm_head]
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+ # lora_dropout: 0.05
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+ # lora_target_linear: true
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+
130
+
131
+ unfrozen_parameters:
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+ - ^lm_head.weight$
133
+ - ^model.embed_tokens.weight$
134
+ - input_layernorm
135
+ - model.norm
136
+ - post_attention_layernorm
137
+ - self_attn.rotary_emb
138
+ # mlp.down_proj layers
139
+ - model.layers.0.mlp.down_proj
140
+ - model.layers.1.mlp.down_proj
141
+ - model.layers.4.mlp.down_proj
142
+ - model.layers.37.mlp.down_proj
143
+ - model.layers.24.mlp.down_proj
144
+ - model.layers.2.mlp.down_proj
145
+ - model.layers.38.mlp.down_proj
146
+ - model.layers.35.mlp.down_proj
147
+ - model.layers.25.mlp.down_proj
148
+ - model.layers.6.mlp.down_proj
149
+ - model.layers.22.mlp.down_proj
150
+ - model.layers.23.mlp.down_proj
151
+ - model.layers.3.mlp.down_proj
152
+ - model.layers.21.mlp.down_proj
153
+ - model.layers.5.mlp.down_proj
154
+ - model.layers.28.mlp.down_proj
155
+ - model.layers.20.mlp.down_proj
156
+ - model.layers.26.mlp.down_proj
157
+ - model.layers.19.mlp.down_proj
158
+ - model.layers.34.mlp.down_proj
159
+ # mlp.gate_proj layers
160
+ - model.layers.2.mlp.gate_proj
161
+ - model.layers.1.mlp.gate_proj
162
+ - model.layers.3.mlp.gate_proj
163
+ - model.layers.5.mlp.gate_proj
164
+ - model.layers.4.mlp.gate_proj
165
+ - model.layers.35.mlp.gate_proj
166
+ - model.layers.36.mlp.gate_proj
167
+ - model.layers.37.mlp.gate_proj
168
+ - model.layers.38.mlp.gate_proj
169
+ - model.layers.34.mlp.gate_proj
170
+ - model.layers.33.mlp.gate_proj
171
+ - model.layers.8.mlp.gate_proj
172
+ - model.layers.32.mlp.gate_proj
173
+ - model.layers.6.mlp.gate_proj
174
+ - model.layers.28.mlp.gate_proj
175
+ - model.layers.26.mlp.gate_proj
176
+ - model.layers.30.mlp.gate_proj
177
+ - model.layers.23.mlp.gate_proj
178
+ - model.layers.29.mlp.gate_proj
179
+ - model.layers.27.mlp.gate_proj
180
+ # mlp.up_proj layers
181
+ - model.layers.3.mlp.up_proj
182
+ - model.layers.4.mlp.up_proj
183
+ - model.layers.6.mlp.up_proj
184
+ - model.layers.2.mlp.up_proj
185
+ - model.layers.5.mlp.up_proj
186
+ - model.layers.8.mlp.up_proj
187
+ - model.layers.10.mlp.up_proj
188
+ - model.layers.9.mlp.up_proj
189
+ - model.layers.7.mlp.up_proj
190
+ - model.layers.0.mlp.up_proj
191
+ - model.layers.17.mlp.up_proj
192
+ - model.layers.15.mlp.up_proj
193
+ - model.layers.22.mlp.up_proj
194
+ - model.layers.18.mlp.up_proj
195
+ - model.layers.16.mlp.up_proj
196
+ - model.layers.11.mlp.up_proj
197
+ - model.layers.21.mlp.up_proj
198
+ - model.layers.23.mlp.up_proj
199
+ - model.layers.20.mlp.up_proj
200
+ - model.layers.27.mlp.up_proj
201
+ # self_attn.k_proj layers
202
+ - model.layers.30.self_attn.k_proj
203
+ - model.layers.27.self_attn.k_proj
204
+ - model.layers.25.self_attn.k_proj
205
+ - model.layers.33.self_attn.k_proj
206
+ - model.layers.26.self_attn.k_proj
207
+ - model.layers.31.self_attn.k_proj
208
+ - model.layers.35.self_attn.k_proj
209
+ - model.layers.39.self_attn.k_proj
210
+ - model.layers.22.self_attn.k_proj
211
+ - model.layers.24.self_attn.k_proj
212
+ - model.layers.21.self_attn.k_proj
213
+ - model.layers.28.self_attn.k_proj
214
+ - model.layers.23.self_attn.k_proj
215
+ - model.layers.36.self_attn.k_proj
216
+ - model.layers.20.self_attn.k_proj
217
+ - model.layers.37.self_attn.k_proj
218
+ - model.layers.29.self_attn.k_proj
219
+ - model.layers.32.self_attn.k_proj
220
+ - model.layers.16.self_attn.k_proj
221
+ - model.layers.18.self_attn.k_proj
222
+ # self_attn.o_proj layers
223
+ - model.layers.7.self_attn.o_proj
224
+ - model.layers.6.self_attn.o_proj
225
+ - model.layers.9.self_attn.o_proj
226
+ - model.layers.5.self_attn.o_proj
227
+ - model.layers.27.self_attn.o_proj
228
+ - model.layers.26.self_attn.o_proj
229
+ - model.layers.4.self_attn.o_proj
230
+ - model.layers.31.self_attn.o_proj
231
+ - model.layers.8.self_attn.o_proj
232
+ - model.layers.16.self_attn.o_proj
233
+ - model.layers.3.self_attn.o_proj
234
+ - model.layers.10.self_attn.o_proj
235
+ - model.layers.18.self_attn.o_proj
236
+ - model.layers.33.self_attn.o_proj
237
+ - model.layers.17.self_attn.o_proj
238
+ - model.layers.32.self_attn.o_proj
239
+ - model.layers.30.self_attn.o_proj
240
+ - model.layers.2.self_attn.o_proj
241
+ - model.layers.15.self_attn.o_proj
242
+ - model.layers.11.self_attn.o_proj
243
+ # self_attn.q_proj layers
244
+ - model.layers.14.self_attn.q_proj
245
+ - model.layers.11.self_attn.q_proj
246
+ - model.layers.15.self_attn.q_proj
247
+ - model.layers.9.self_attn.q_proj
248
+ - model.layers.8.self_attn.q_proj
249
+ - model.layers.18.self_attn.q_proj
250
+ - model.layers.12.self_attn.q_proj
251
+ - model.layers.13.self_attn.q_proj
252
+ - model.layers.19.self_attn.q_proj
253
+ - model.layers.16.self_attn.q_proj
254
+ - model.layers.10.self_attn.q_proj
255
+ - model.layers.17.self_attn.q_proj
256
+ - model.layers.7.self_attn.q_proj
257
+ - model.layers.5.self_attn.q_proj
258
+ - model.layers.20.self_attn.q_proj
259
+ - model.layers.3.self_attn.q_proj
260
+ - model.layers.26.self_attn.q_proj
261
+ - model.layers.27.self_attn.q_proj
262
+ - model.layers.28.self_attn.q_proj
263
+ - model.layers.33.self_attn.q_proj
264
+ # self_attn.v_proj layers
265
+ - model.layers.27.self_attn.v_proj
266
+ - model.layers.20.self_attn.v_proj
267
+ - model.layers.24.self_attn.v_proj
268
+ - model.layers.25.self_attn.v_proj
269
+ - model.layers.30.self_attn.v_proj
270
+ - model.layers.2.self_attn.v_proj
271
+ - model.layers.23.self_attn.v_proj
272
+ - model.layers.22.self_attn.v_proj
273
+ - model.layers.26.self_attn.v_proj
274
+ - model.layers.33.self_attn.v_proj
275
+ - model.layers.37.self_attn.v_proj
276
+ - model.layers.7.self_attn.v_proj
277
+ - model.layers.4.self_attn.v_proj
278
+ - model.layers.18.self_attn.v_proj
279
+ - model.layers.31.self_attn.v_proj
280
+ - model.layers.17.self_attn.v_proj
281
+ - model.layers.35.self_attn.v_proj
282
+ - model.layers.32.self_attn.v_proj
283
+ - model.layers.21.self_attn.v_proj
284
+ - model.layers.3.self_attn.v_proj
285
+
286
+
287
+
288
+ dataset_prepared_path: /workspace/axolotl/dolph-2.9.3-nemo-prepared
289
+ val_set_size: 0.01
290
+ output_dir: /workspace/axolotl/dolphin-2.9.3-mistral-nemo
291
+
292
+ sequence_len: 8192
293
+ sample_packing: true
294
+ pad_to_sequence_len: true
295
+
296
+ wandb_project: dolphin-2.9.3-Mistral-nemo
297
+ wandb_watch:
298
+ wandb_run_id:
299
+ wandb_log_model:
300
+
301
+ gradient_accumulation_steps: 16
302
+ micro_batch_size: 1
303
+ num_epochs: 3
304
+ optimizer: adamw_torch
305
+ lr_scheduler: cosine
306
+ learning_rate: 5e-6
307
+ train_on_inputs: false
308
+ group_by_length: false
309
+ bf16: auto
310
+ fp16:
311
+ tf32:
312
+
313
+ gradient_checkpointing: true
314
+ gradient_checkpointing_kwargs:
315
+ use_reentrant: false
316
+ early_stopping_patience:
317
+ resume_from_checkpoint:
318
+ logging_steps: 1
319
+ xformers_attention:
320
+ flash_attention: true
321
+
322
+ warmup_steps: 100
323
+ # evals_per_epoch: 4
324
+ eval_table_size:
325
+ saves_per_epoch: 1
326
+ save_total_limit: 2
327
+ save_steps:
328
+ debug:
329
+ deepspeed: deepspeed_configs/zero3_bf16.json
330
+ weight_decay: 0.1
331
+ special_tokens:
332
+ eos_token: "<|im_end|>"
333
+ pad_token: "<pad>"
334
+ bos_token: "<s>"
335
+ unk_token: "<unk>"
336
+ tokens:
337
+ - "<|im_start|>"
338
+
339
+
340
+ # fsdp:
341
+ # - full_shard
342
+ # - auto_wrap
343
+ # fsdp_config:
344
+ # fsdp_limit_all_gathers: true
345
+ # fsdp_sync_module_states: true
346
+ # fsdp_offload_params: true
347
+ # fsdp_use_orig_params: false
348
+ # fsdp_cpu_ram_efficient_loading: true
349
+ # fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
350
+ # fsdp_state_dict_type: FULL_STATE_DICT
351
+ # fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
352
+ # fsdp_sharding_strategy: FULL_SHARD
353
+ # fsdp_forward_prefetch: false
354
+ # fsdp_backward_prefetch: BACKWARD_PRE
355
+ ```
356
+
357
+ </details><br>
358
+
359
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ehartford/dolphin-2.9.3-Mistral-nemo/runs/c23odyoj)
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+ # workspace/axolotl/dolphin-2.9.3-mistral-nemo
361
+
362
+ This model was trained from scratch on the None dataset.
363
+ It achieves the following results on the evaluation set:
364
+ - Loss: 0.5605
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+
366
+ ## Model description
367
+
368
+ More information needed
369
+
370
+ ## Intended uses & limitations
371
+
372
+ More information needed
373
+
374
+ ## Training and evaluation data
375
+
376
+ More information needed
377
+
378
+ ## Training procedure
379
+
380
+ ### Training hyperparameters
381
+
382
+ The following hyperparameters were used during training:
383
+ - learning_rate: 5e-06
384
+ - train_batch_size: 1
385
+ - eval_batch_size: 1
386
+ - seed: 42
387
+ - distributed_type: multi-GPU
388
+ - num_devices: 8
389
+ - gradient_accumulation_steps: 16
390
+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 8
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
393
+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 100
395
+ - num_epochs: 3
396
+
397
+ ### Training results
398
+
399
+ | Training Loss | Epoch | Step | Validation Loss |
400
+ |:-------------:|:------:|:----:|:---------------:|
401
+ | 0.5691 | 1.0162 | 983 | 0.5734 |
402
+ | 0.5335 | 2.0174 | 1968 | 0.5609 |
403
+ | 0.5297 | 2.9639 | 2901 | 0.5605 |
404
+
405
+
406
+ ### Framework versions
407
+
408
+ - Transformers 4.43.0.dev0
409
+ - Pytorch 2.2.2+cu121
410
+ - Datasets 2.19.1
411
+ - Tokenizers 0.19.1
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+ "content": "<pad>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "unk_token": {
24
+ "content": "<unk>",
25
+ "lstrip": false,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ }
30
+ }
tokenizer.json ADDED
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tokenizer_config.json ADDED
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vocab.json ADDED
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