NeoChen1024
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Browse files- README.md +485 -0
- added_tokens.json +4 -0
- config.json +38 -0
- generation_config.json +7 -0
- measurement.json +0 -0
- model.safetensors.index.json +370 -0
- output-00001-of-00002.safetensors +3 -0
- output-00002-of-00002.safetensors +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +0 -0
- vocab.json +0 -0
README.md
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1 |
+
---
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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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# Dolphin 2.9.3 Mistral Nemo 12b 🐬
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Curated and trained by Eric Hartford and Cognitive Computations
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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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<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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This model is based on mistralai/Mistral-Nemo-Base-2407, and is governed by the apache 2.0 license.
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The base model has 128K context, and our finetuning used 8192 sequence length.
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Dolphin 2.9.3 uses ChatML prompt template format.
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example:
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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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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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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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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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## Evals
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<details><summary>See evals</summary>
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```
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+
| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr|
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|-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|
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|leaderboard |N/A |none | 0|acc |↑ |0.3437|± |0.0043|
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| | |none | 0|acc_norm |↑ |0.5076|± |0.0053|
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| | |none | 0|exact_match |↑ |0.0536|± |0.0061|
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| | |none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A |
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| | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A |
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| | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199|
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| | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186|
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| - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.5549|± |0.0061|
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| - leaderboard_bbh_boolean_expressions | 0|none | 3|acc_norm |↑ |0.8640|± |0.0217|
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| - leaderboard_bbh_causal_judgement | 0|none | 3|acc_norm |↑ |0.6417|± |0.0352|
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| - leaderboard_bbh_date_understanding | 0|none | 3|acc_norm |↑ |0.6080|± |0.0309|
|
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+
| - leaderboard_bbh_disambiguation_qa | 0|none | 3|acc_norm |↑ |0.6480|± |0.0303|
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+
| - leaderboard_bbh_formal_fallacies | 0|none | 3|acc_norm |↑ |0.5360|± |0.0316|
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+
| - leaderboard_bbh_geometric_shapes | 0|none | 3|acc_norm |↑ |0.5240|± |0.0316|
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| - leaderboard_bbh_hyperbaton | 0|none | 3|acc_norm |↑ |0.6440|± |0.0303|
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| - leaderboard_bbh_logical_deduction_five_objects | 0|none | 3|acc_norm |↑ |0.4600|± |0.0316|
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| - leaderboard_bbh_logical_deduction_seven_objects | 0|none | 3|acc_norm |↑ |0.4680|± |0.0316|
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| - leaderboard_bbh_logical_deduction_three_objects | 0|none | 3|acc_norm |↑ |0.7000|± |0.0290|
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+
| - leaderboard_bbh_movie_recommendation | 0|none | 3|acc_norm |↑ |0.8160|± |0.0246|
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| - leaderboard_bbh_navigate | 0|none | 3|acc_norm |↑ |0.6040|± |0.0310|
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| - leaderboard_bbh_object_counting | 0|none | 3|acc_norm |↑ |0.3680|± |0.0306|
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| - leaderboard_bbh_penguins_in_a_table | 0|none | 3|acc_norm |↑ |0.5548|± |0.0413|
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| - leaderboard_bbh_reasoning_about_colored_objects | 0|none | 3|acc_norm |↑ |0.6320|± |0.0306|
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| - leaderboard_bbh_ruin_names | 0|none | 3|acc_norm |↑ |0.7440|± |0.0277|
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| - leaderboard_bbh_salient_translation_error_detection | 0|none | 3|acc_norm |↑ |0.5280|± |0.0316|
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| - leaderboard_bbh_snarks | 0|none | 3|acc_norm |↑ |0.6292|± |0.0363|
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| - leaderboard_bbh_sports_understanding | 0|none | 3|acc_norm |↑ |0.8040|± |0.0252|
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| - leaderboard_bbh_temporal_sequences | 0|none | 3|acc_norm |↑ |0.4680|± |0.0316|
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| - leaderboard_bbh_tracking_shuffled_objects_five_objects | 0|none | 3|acc_norm |↑ |0.2160|± |0.0261|
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| - leaderboard_bbh_tracking_shuffled_objects_seven_objects| 0|none | 3|acc_norm |↑ |0.1160|± |0.0203|
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| - leaderboard_bbh_tracking_shuffled_objects_three_objects| 0|none | 3|acc_norm |↑ |0.3000|± |0.0290|
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| - leaderboard_bbh_web_of_lies | 0|none | 3|acc_norm |↑ |0.4880|± |0.0317|
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+
| - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.3146|± |0.0135|
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+
| - leaderboard_gpqa_diamond | 1|none | 0|acc_norm |↑ |0.3182|± |0.0332|
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| - leaderboard_gpqa_extended | 1|none | 0|acc_norm |↑ |0.3187|± |0.0200|
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| - leaderboard_gpqa_main | 1|none | 0|acc_norm |↑ |0.3080|± |0.0218|
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| - leaderboard_ifeval | 2|none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A |
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| | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A |
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| | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199|
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| | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186|
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| - leaderboard_math_algebra_hard | 1|none | 4|exact_match |↑ |0.0749|± |0.0150|
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| - leaderboard_math_counting_and_prob_hard | 1|none | 4|exact_match |↑ |0.0244|± |0.0140|
|
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| - leaderboard_math_geometry_hard | 1|none | 4|exact_match |↑ |0.0227|± |0.0130|
|
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| - leaderboard_math_hard |N/A |none | 4|exact_match |↑ |0.0536|± |0.0061|
|
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+
| - leaderboard_math_intermediate_algebra_hard | 1|none | 4|exact_match |↑ |0.0250|± |0.0093|
|
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+
| - leaderboard_math_num_theory_hard | 1|none | 4|exact_match |↑ |0.0390|± |0.0156|
|
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+
| - leaderboard_math_prealgebra_hard | 1|none | 4|exact_match |↑ |0.1295|± |0.0242|
|
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| - leaderboard_math_precalculus_hard | 1|none | 4|exact_match |↑ |0.0296|± |0.0146|
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| - leaderboard_mmlu_pro | 0.1|none | 5|acc |↑ |0.3437|± |0.0043|
|
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| - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.4511|± |0.0178|
|
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| - leaderboard_musr_murder_mysteries | 1|none | 0|acc_norm |↑ |0.5880|± |0.0312|
|
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+
| - leaderboard_musr_object_placements | 1|none | 0|acc_norm |↑ |0.3438|± |0.0297|
|
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+
| - leaderboard_musr_team_allocation | 1|none | 0|acc_norm |↑ |0.4240|± |0.0313|
|
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+
|
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| Groups |Version|Filter|n-shot| Metric | |Value | |Stderr|
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|------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|
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|leaderboard |N/A |none | 0|acc |↑ |0.3437|± |0.0043|
|
117 |
+
| | |none | 0|acc_norm |↑ |0.5076|± |0.0053|
|
118 |
+
| | |none | 0|exact_match |↑ |0.0536|± |0.0061|
|
119 |
+
| | |none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A |
|
120 |
+
| | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A |
|
121 |
+
| | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199|
|
122 |
+
| | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186|
|
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+
| - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.5549|± |0.0061|
|
124 |
+
| - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.3146|± |0.0135|
|
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+
| - leaderboard_math_hard|N/A |none | 4|exact_match |↑ |0.0536|± |0.0061|
|
126 |
+
| - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.4511|± |0.0178|
|
127 |
+
```
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</details><br>
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## Training
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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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[<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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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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load_in_8bit: false
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# load_in_4bit: true
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strict: false
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datasets:
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+
- path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl
|
151 |
+
type: sharegpt
|
152 |
+
conversation: chatml
|
153 |
+
- path: /workspace/datasets/dolphin-2.9.3/SystemChat_filtered_sharegpt.jsonl
|
154 |
+
type: sharegpt
|
155 |
+
conversation: chatml
|
156 |
+
- path: /workspace/datasets/dolphin-2.9.3/SystemChat_multilingual_sharegpt.jsonl
|
157 |
+
type: sharegpt
|
158 |
+
conversation: chatml
|
159 |
+
- path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-translate-sharegpt2.jsonl
|
160 |
+
type: sharegpt
|
161 |
+
conversation: chatml
|
162 |
+
- path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-codegen-sharegpt2.jsonl
|
163 |
+
type: sharegpt
|
164 |
+
conversation: chatml
|
165 |
+
- path: /workspace/datasets/dolphin-2.9.3/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
|
166 |
+
type: sharegpt
|
167 |
+
conversation: chatml
|
168 |
+
- path: /workspace/datasets/dolphin-2.9.3/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
|
169 |
+
type: sharegpt
|
170 |
+
conversation: chatml
|
171 |
+
- path: /workspace/datasets/dolphin-2.9.3/not_samantha_norefusals.jsonl
|
172 |
+
type: sharegpt
|
173 |
+
conversation: chatml
|
174 |
+
- path: /workspace/datasets/dolphin-2.9.3/Orca-Math-resort-unfiltered.jsonl
|
175 |
+
type: sharegpt
|
176 |
+
conversation: chatml
|
177 |
+
- path: /workspace/datasets/dolphin-2.9.3/agent_instruct_react_unfiltered.jsonl
|
178 |
+
type: sharegpt
|
179 |
+
conversation: chatml
|
180 |
+
- path: /workspace/datasets/dolphin-2.9.3/toolbench_instruct_j1s1_3k_unfiltered.jsonl
|
181 |
+
type: sharegpt
|
182 |
+
conversation: chatml
|
183 |
+
- path: /workspace/datasets/dolphin-2.9.3/toolbench_negative_unfiltered.jsonl
|
184 |
+
type: sharegpt
|
185 |
+
conversation: chatml
|
186 |
+
- path: /workspace/datasets/dolphin-2.9.3/toolbench_react_10p_unfiltered.jsonl
|
187 |
+
type: sharegpt
|
188 |
+
conversation: chatml
|
189 |
+
- path: /workspace/datasets/dolphin-2.9.3/toolbench_tflan_cot_30p_unfiltered.jsonl
|
190 |
+
type: sharegpt
|
191 |
+
conversation: chatml
|
192 |
+
- path: /workspace/datasets/dolphin-2.9.3/openhermes200k_unfiltered.jsonl
|
193 |
+
type: sharegpt
|
194 |
+
conversation: chatml
|
195 |
+
|
196 |
+
chat_template: chatml
|
197 |
+
# adapter: qlora
|
198 |
+
# lora_r: 128
|
199 |
+
# lora_alpha: 16
|
200 |
+
# lora_modules_to_save: [embed_tokens, lm_head]
|
201 |
+
# lora_dropout: 0.05
|
202 |
+
# lora_target_linear: true
|
203 |
+
|
204 |
+
|
205 |
+
unfrozen_parameters:
|
206 |
+
- ^lm_head.weight$
|
207 |
+
- ^model.embed_tokens.weight$
|
208 |
+
- input_layernorm
|
209 |
+
- model.norm
|
210 |
+
- post_attention_layernorm
|
211 |
+
- self_attn.rotary_emb
|
212 |
+
# mlp.down_proj layers
|
213 |
+
- model.layers.0.mlp.down_proj
|
214 |
+
- model.layers.1.mlp.down_proj
|
215 |
+
- model.layers.4.mlp.down_proj
|
216 |
+
- model.layers.37.mlp.down_proj
|
217 |
+
- model.layers.24.mlp.down_proj
|
218 |
+
- model.layers.2.mlp.down_proj
|
219 |
+
- model.layers.38.mlp.down_proj
|
220 |
+
- model.layers.35.mlp.down_proj
|
221 |
+
- model.layers.25.mlp.down_proj
|
222 |
+
- model.layers.6.mlp.down_proj
|
223 |
+
- model.layers.22.mlp.down_proj
|
224 |
+
- model.layers.23.mlp.down_proj
|
225 |
+
- model.layers.3.mlp.down_proj
|
226 |
+
- model.layers.21.mlp.down_proj
|
227 |
+
- model.layers.5.mlp.down_proj
|
228 |
+
- model.layers.28.mlp.down_proj
|
229 |
+
- model.layers.20.mlp.down_proj
|
230 |
+
- model.layers.26.mlp.down_proj
|
231 |
+
- model.layers.19.mlp.down_proj
|
232 |
+
- model.layers.34.mlp.down_proj
|
233 |
+
# mlp.gate_proj layers
|
234 |
+
- model.layers.2.mlp.gate_proj
|
235 |
+
- model.layers.1.mlp.gate_proj
|
236 |
+
- model.layers.3.mlp.gate_proj
|
237 |
+
- model.layers.5.mlp.gate_proj
|
238 |
+
- model.layers.4.mlp.gate_proj
|
239 |
+
- model.layers.35.mlp.gate_proj
|
240 |
+
- model.layers.36.mlp.gate_proj
|
241 |
+
- model.layers.37.mlp.gate_proj
|
242 |
+
- model.layers.38.mlp.gate_proj
|
243 |
+
- model.layers.34.mlp.gate_proj
|
244 |
+
- model.layers.33.mlp.gate_proj
|
245 |
+
- model.layers.8.mlp.gate_proj
|
246 |
+
- model.layers.32.mlp.gate_proj
|
247 |
+
- model.layers.6.mlp.gate_proj
|
248 |
+
- model.layers.28.mlp.gate_proj
|
249 |
+
- model.layers.26.mlp.gate_proj
|
250 |
+
- model.layers.30.mlp.gate_proj
|
251 |
+
- model.layers.23.mlp.gate_proj
|
252 |
+
- model.layers.29.mlp.gate_proj
|
253 |
+
- model.layers.27.mlp.gate_proj
|
254 |
+
# mlp.up_proj layers
|
255 |
+
- model.layers.3.mlp.up_proj
|
256 |
+
- model.layers.4.mlp.up_proj
|
257 |
+
- model.layers.6.mlp.up_proj
|
258 |
+
- model.layers.2.mlp.up_proj
|
259 |
+
- model.layers.5.mlp.up_proj
|
260 |
+
- model.layers.8.mlp.up_proj
|
261 |
+
- model.layers.10.mlp.up_proj
|
262 |
+
- model.layers.9.mlp.up_proj
|
263 |
+
- model.layers.7.mlp.up_proj
|
264 |
+
- model.layers.0.mlp.up_proj
|
265 |
+
- model.layers.17.mlp.up_proj
|
266 |
+
- model.layers.15.mlp.up_proj
|
267 |
+
- model.layers.22.mlp.up_proj
|
268 |
+
- model.layers.18.mlp.up_proj
|
269 |
+
- model.layers.16.mlp.up_proj
|
270 |
+
- model.layers.11.mlp.up_proj
|
271 |
+
- model.layers.21.mlp.up_proj
|
272 |
+
- model.layers.23.mlp.up_proj
|
273 |
+
- model.layers.20.mlp.up_proj
|
274 |
+
- model.layers.27.mlp.up_proj
|
275 |
+
# self_attn.k_proj layers
|
276 |
+
- model.layers.30.self_attn.k_proj
|
277 |
+
- model.layers.27.self_attn.k_proj
|
278 |
+
- model.layers.25.self_attn.k_proj
|
279 |
+
- model.layers.33.self_attn.k_proj
|
280 |
+
- model.layers.26.self_attn.k_proj
|
281 |
+
- model.layers.31.self_attn.k_proj
|
282 |
+
- model.layers.35.self_attn.k_proj
|
283 |
+
- model.layers.39.self_attn.k_proj
|
284 |
+
- model.layers.22.self_attn.k_proj
|
285 |
+
- model.layers.24.self_attn.k_proj
|
286 |
+
- model.layers.21.self_attn.k_proj
|
287 |
+
- model.layers.28.self_attn.k_proj
|
288 |
+
- model.layers.23.self_attn.k_proj
|
289 |
+
- model.layers.36.self_attn.k_proj
|
290 |
+
- model.layers.20.self_attn.k_proj
|
291 |
+
- model.layers.37.self_attn.k_proj
|
292 |
+
- model.layers.29.self_attn.k_proj
|
293 |
+
- model.layers.32.self_attn.k_proj
|
294 |
+
- model.layers.16.self_attn.k_proj
|
295 |
+
- model.layers.18.self_attn.k_proj
|
296 |
+
# self_attn.o_proj layers
|
297 |
+
- model.layers.7.self_attn.o_proj
|
298 |
+
- model.layers.6.self_attn.o_proj
|
299 |
+
- model.layers.9.self_attn.o_proj
|
300 |
+
- model.layers.5.self_attn.o_proj
|
301 |
+
- model.layers.27.self_attn.o_proj
|
302 |
+
- model.layers.26.self_attn.o_proj
|
303 |
+
- model.layers.4.self_attn.o_proj
|
304 |
+
- model.layers.31.self_attn.o_proj
|
305 |
+
- model.layers.8.self_attn.o_proj
|
306 |
+
- model.layers.16.self_attn.o_proj
|
307 |
+
- model.layers.3.self_attn.o_proj
|
308 |
+
- model.layers.10.self_attn.o_proj
|
309 |
+
- model.layers.18.self_attn.o_proj
|
310 |
+
- model.layers.33.self_attn.o_proj
|
311 |
+
- model.layers.17.self_attn.o_proj
|
312 |
+
- model.layers.32.self_attn.o_proj
|
313 |
+
- model.layers.30.self_attn.o_proj
|
314 |
+
- model.layers.2.self_attn.o_proj
|
315 |
+
- model.layers.15.self_attn.o_proj
|
316 |
+
- model.layers.11.self_attn.o_proj
|
317 |
+
# self_attn.q_proj layers
|
318 |
+
- model.layers.14.self_attn.q_proj
|
319 |
+
- model.layers.11.self_attn.q_proj
|
320 |
+
- model.layers.15.self_attn.q_proj
|
321 |
+
- model.layers.9.self_attn.q_proj
|
322 |
+
- model.layers.8.self_attn.q_proj
|
323 |
+
- model.layers.18.self_attn.q_proj
|
324 |
+
- model.layers.12.self_attn.q_proj
|
325 |
+
- model.layers.13.self_attn.q_proj
|
326 |
+
- model.layers.19.self_attn.q_proj
|
327 |
+
- model.layers.16.self_attn.q_proj
|
328 |
+
- model.layers.10.self_attn.q_proj
|
329 |
+
- model.layers.17.self_attn.q_proj
|
330 |
+
- model.layers.7.self_attn.q_proj
|
331 |
+
- model.layers.5.self_attn.q_proj
|
332 |
+
- model.layers.20.self_attn.q_proj
|
333 |
+
- model.layers.3.self_attn.q_proj
|
334 |
+
- model.layers.26.self_attn.q_proj
|
335 |
+
- model.layers.27.self_attn.q_proj
|
336 |
+
- model.layers.28.self_attn.q_proj
|
337 |
+
- model.layers.33.self_attn.q_proj
|
338 |
+
# self_attn.v_proj layers
|
339 |
+
- model.layers.27.self_attn.v_proj
|
340 |
+
- model.layers.20.self_attn.v_proj
|
341 |
+
- model.layers.24.self_attn.v_proj
|
342 |
+
- model.layers.25.self_attn.v_proj
|
343 |
+
- model.layers.30.self_attn.v_proj
|
344 |
+
- model.layers.2.self_attn.v_proj
|
345 |
+
- model.layers.23.self_attn.v_proj
|
346 |
+
- model.layers.22.self_attn.v_proj
|
347 |
+
- model.layers.26.self_attn.v_proj
|
348 |
+
- model.layers.33.self_attn.v_proj
|
349 |
+
- model.layers.37.self_attn.v_proj
|
350 |
+
- model.layers.7.self_attn.v_proj
|
351 |
+
- model.layers.4.self_attn.v_proj
|
352 |
+
- model.layers.18.self_attn.v_proj
|
353 |
+
- model.layers.31.self_attn.v_proj
|
354 |
+
- model.layers.17.self_attn.v_proj
|
355 |
+
- model.layers.35.self_attn.v_proj
|
356 |
+
- model.layers.32.self_attn.v_proj
|
357 |
+
- model.layers.21.self_attn.v_proj
|
358 |
+
- model.layers.3.self_attn.v_proj
|
359 |
+
|
360 |
+
|
361 |
+
|
362 |
+
dataset_prepared_path: /workspace/axolotl/dolph-2.9.3-nemo-prepared
|
363 |
+
val_set_size: 0.01
|
364 |
+
output_dir: /workspace/axolotl/dolphin-2.9.3-mistral-nemo
|
365 |
+
|
366 |
+
sequence_len: 8192
|
367 |
+
sample_packing: true
|
368 |
+
pad_to_sequence_len: true
|
369 |
+
|
370 |
+
wandb_project: dolphin-2.9.3-Mistral-nemo
|
371 |
+
wandb_watch:
|
372 |
+
wandb_run_id:
|
373 |
+
wandb_log_model:
|
374 |
+
|
375 |
+
gradient_accumulation_steps: 16
|
376 |
+
micro_batch_size: 1
|
377 |
+
num_epochs: 3
|
378 |
+
optimizer: adamw_torch
|
379 |
+
lr_scheduler: cosine
|
380 |
+
learning_rate: 5e-6
|
381 |
+
train_on_inputs: false
|
382 |
+
group_by_length: false
|
383 |
+
bf16: auto
|
384 |
+
fp16:
|
385 |
+
tf32:
|
386 |
+
|
387 |
+
gradient_checkpointing: true
|
388 |
+
gradient_checkpointing_kwargs:
|
389 |
+
use_reentrant: false
|
390 |
+
early_stopping_patience:
|
391 |
+
resume_from_checkpoint:
|
392 |
+
logging_steps: 1
|
393 |
+
xformers_attention:
|
394 |
+
flash_attention: true
|
395 |
+
|
396 |
+
warmup_steps: 100
|
397 |
+
# evals_per_epoch: 4
|
398 |
+
eval_table_size:
|
399 |
+
saves_per_epoch: 1
|
400 |
+
save_total_limit: 2
|
401 |
+
save_steps:
|
402 |
+
debug:
|
403 |
+
deepspeed: deepspeed_configs/zero3_bf16.json
|
404 |
+
weight_decay: 0.1
|
405 |
+
special_tokens:
|
406 |
+
eos_token: "<|im_end|>"
|
407 |
+
pad_token: "<pad>"
|
408 |
+
bos_token: "<s>"
|
409 |
+
unk_token: "<unk>"
|
410 |
+
tokens:
|
411 |
+
- "<|im_start|>"
|
412 |
+
|
413 |
+
|
414 |
+
# fsdp:
|
415 |
+
# - full_shard
|
416 |
+
# - auto_wrap
|
417 |
+
# fsdp_config:
|
418 |
+
# fsdp_limit_all_gathers: true
|
419 |
+
# fsdp_sync_module_states: true
|
420 |
+
# fsdp_offload_params: true
|
421 |
+
# fsdp_use_orig_params: false
|
422 |
+
# fsdp_cpu_ram_efficient_loading: true
|
423 |
+
# fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
|
424 |
+
# fsdp_state_dict_type: FULL_STATE_DICT
|
425 |
+
# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
|
426 |
+
# fsdp_sharding_strategy: FULL_SHARD
|
427 |
+
# fsdp_forward_prefetch: false
|
428 |
+
# fsdp_backward_prefetch: BACKWARD_PRE
|
429 |
+
```
|
430 |
+
|
431 |
+
</details><br>
|
432 |
+
|
433 |
+
[<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)
|
434 |
+
# workspace/axolotl/dolphin-2.9.3-mistral-nemo
|
435 |
+
|
436 |
+
This model was trained from scratch on the None dataset.
|
437 |
+
It achieves the following results on the evaluation set:
|
438 |
+
- Loss: 0.5605
|
439 |
+
|
440 |
+
## Model description
|
441 |
+
|
442 |
+
More information needed
|
443 |
+
|
444 |
+
## Intended uses & limitations
|
445 |
+
|
446 |
+
More information needed
|
447 |
+
|
448 |
+
## Training and evaluation data
|
449 |
+
|
450 |
+
More information needed
|
451 |
+
|
452 |
+
## Training procedure
|
453 |
+
|
454 |
+
### Training hyperparameters
|
455 |
+
|
456 |
+
The following hyperparameters were used during training:
|
457 |
+
- learning_rate: 5e-06
|
458 |
+
- train_batch_size: 1
|
459 |
+
- eval_batch_size: 1
|
460 |
+
- seed: 42
|
461 |
+
- distributed_type: multi-GPU
|
462 |
+
- num_devices: 8
|
463 |
+
- gradient_accumulation_steps: 16
|
464 |
+
- total_train_batch_size: 128
|
465 |
+
- total_eval_batch_size: 8
|
466 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
467 |
+
- lr_scheduler_type: cosine
|
468 |
+
- lr_scheduler_warmup_steps: 100
|
469 |
+
- num_epochs: 3
|
470 |
+
|
471 |
+
### Training results
|
472 |
+
|
473 |
+
| Training Loss | Epoch | Step | Validation Loss |
|
474 |
+
|:-------------:|:------:|:----:|:---------------:|
|
475 |
+
| 0.5691 | 1.0162 | 983 | 0.5734 |
|
476 |
+
| 0.5335 | 2.0174 | 1968 | 0.5609 |
|
477 |
+
| 0.5297 | 2.9639 | 2901 | 0.5605 |
|
478 |
+
|
479 |
+
|
480 |
+
### Framework versions
|
481 |
+
|
482 |
+
- Transformers 4.43.0.dev0
|
483 |
+
- Pytorch 2.2.2+cu121
|
484 |
+
- Datasets 2.19.1
|
485 |
+
- Tokenizers 0.19.1
|
added_tokens.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"<|im_end|>": 131072,
|
3 |
+
"<|im_start|>": 131073
|
4 |
+
}
|
config.json
ADDED
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
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