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README.md

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+---
+license: other
+tags:
+- axolotl
+- finetune
+- qlora
+base_model: openchat/openchat-3.5-0106
+datasets:
+- hendrycks/competition_math
+- allenai/ai2_arc
+- camel-ai/physics
+- camel-ai/chemistry
+- camel-ai/biology
+- camel-ai/math
+- STEM-AI-mtl/Electrical-engineering
+- openbookqa
+- piqa
+- metaeval/reclor
+- mandyyyyii/scibench
+- derek-thomas/ScienceQA
+- sciq
+- TIGER-Lab/ScienceEval
+---
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/aimTTdmut59aZxOWQlkcC.jpeg)
+
+# 🔬👩‍🔬 Newton-7B
+
+This model is a fine-tuned version of [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) on datasets related to science.
+
+This model is fine-tuned using [QLoRa](https://arxiv.org/abs/2305.14314) and [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl).
+
+This model's training was sponsored by [sablo.ai](https://sablo.ai).
+
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.3.0`
+```yaml
+base_model: openchat/openchat-3.5-0106
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+is_mistral_derived_model: true
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+
+datasets:
+  - path: merged_all.json
+    type:
+      field_instruction: instruction
+      field_output: output
+
+      format: "GPT4 Correct User: {instruction}<|end_of_turn|>GPT4 Correct Assistant:"
+      no_input_format: "GPT4 Correct User: {instruction}<|end_of_turn|>GPT4 Correct Assistant:"
+
+
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.01 # not sure
+output_dir: ./newton
+
+adapter: qlora
+lora_model_dir:
+
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+
+lora_r: 128
+lora_alpha: 64
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_target_modules:
+  - gate_proj
+  - down_proj
+  - up_proj
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+lora_modules_to_save:
+  - embed_tokens
+  - lm_head
+
+wandb_project: huggingface
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+hub_model_id: Weyaxi/newton-lora
+save_safetensors: true
+
+# change #
+gradient_accumulation_steps: 12
+micro_batch_size: 6
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+# change #
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 10 # not sure
+
+saves_per_epoch: 2
+
+evals_per_epoch: 4
+eval_table_size:
+eval_table_max_new_tokens: 128
+
+debug:
+deepspeed:
+weight_decay: 0.1 # not sure
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
+tokens:
+  - "<|end_of_turn|>"
+  - "<|pad_0|>"
+```
+
+</details><br>
+
+# 📊 Datasets
+
+You can find the dataset I used and the work I am doing with this datasets here:
+
+https://huggingface.co/datasets/Weyaxi/sci-datasets
+
+Following datasets were used in this model:
+
+- 📐 [MATH](https://huggingface.co/datasets/hendrycks/competition_math)
+
+- 🧠 [ARC](https://huggingface.co/datasets/allenai/ai2_arc) (Note: Only **train** part)
+
+- 🧲 [camel-ai/physics](https://huggingface.co/datasets/camel-ai/physics)
+
+- ⚗️ [camel-ai/chemistry](https://huggingface.co/datasets/camel-ai/chemistry)
+
+- 🦠 [camel-ai/biology](https://huggingface.co/datasets/camel-ai/biology)
+
+- 📊 [camel-ai/math](https://huggingface.co/datasets/camel-ai/math)
+
+- ⚡ [STEM-AI-mtl/Electrical-engineering](https://huggingface.co/datasets/STEM-AI-mtl/Electrical-engineering)
+
+- 📚 [openbookqa](https://huggingface.co/datasets/openbookqa)
+
+- 🧠 [piqa](https://huggingface.co/datasets/piqa)
+
+- 🎨 [reclor](https://huggingface.co/datasets/metaeval/reclor)
+
+- 🔬 [scibench](https://github.com/mandyyyyii/scibench)
+
+- 🧪 [ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA)
+
+- 🧬 [sciq](https://huggingface.co/datasets/sciq)
+
+- 📝 [ScienceEval](https://huggingface.co/datasets/TIGER-Lab/ScienceEval)
+
+## 🛠️ Multiple Choice Question & Answer Datasets Conversion Progress
+
+I used [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) to generate a reasonable and logical answer by providing it with the question and the answer key.
+
+I used the [Together AI](https://www.together.ai) API for this task.
+
+The following datasets are converted using this method:
+
+- 🧠 [ARC](https://huggingface.co/datasets/allenai/ai2_arc) (Note: Only **train** part)
+
+- 📚 [openbookqa](https://huggingface.co/datasets/openbookqa)
+
+- 🎨 [reclor](https://huggingface.co/datasets/metaeval/reclor)
+
+- 🧬 [sciq](https://huggingface.co/datasets/sciq)
+
+# 💬 Prompt Template
+
+You can use this prompt template while using the model:
+
+### GPT4 Correct [(Openchat)](https://huggingface.co/openchat/openchat-3.5-0106#conversation-templates)
+
+```
+GPT4 Correct User: {user}<|end_of_turn|>GPT4 Correct Assistant: {asistant}<|end_of_turn|>GPT4 Correct User: {user}<|end_of_turn|>GPT4 Correct Assistant:
+```
+
+You can also utilize the chat template method from the tokenizer config like here:
+
+```python
+messages = [
+    {"role": "user", "content": "Hello"},
+    {"role": "assistant", "content": "Hi"},
+    {"role": "user", "content": "How are you today?"}
+]
+tokens = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
+```
+
+# 🤝 Acknowledgments
+
+Thanks to [openchat](https://huggingface.co/openchat) team for fine-tuning an excellent model that I used as a base model.
+
+Thanks to [@jondurbin](https://huggingface.co/jondurbin) for reformatting codes for some datasets: [bagel/data_sources](https://github.com/jondurbin/bagel/tree/main/bagel/data_sources)
+
+Thanks to [Together AI](https://www.together.ai) for providing everyone with free credits, which I used to generate a dataset in multiple choice to explanations format.
+
+Thanks to [Tim Dettmers](https://huggingface.co/timdettmers) for his excellent [QLoRA](https://arxiv.org/abs/2305.14314) work.
+
+Thanks to all the dataset authors mentioned in the datasets section.
+
+Thanks to [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) for making the repository I used to make this model.
+
+Overall, thanks to all of the open soure AI community! 🚀
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+
+If you would like to support me:
+
+[☕ Buy Me a Coffee](https://www.buymeacoffee.com/weyaxi)

added_tokens.json

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+{
+  "<|end_of_turn|>": 32000,
+  "<|pad_0|>": 32001
+}

config.json

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+{
+  "_name_or_path": "openchat/openchat-3.5-0106",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.0",
+  "use_cache": false,
+  "vocab_size": 32002
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 32000,
+  "max_length": 8192,
+  "pad_token_id": 0,
+  "temperature": 0.5,
+  "transformers_version": "4.37.0"
+}

huggingface-metadata.txt

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+url: https://huggingface.co/Weyaxi/Newton-7B
+branch: main
+download date: 2024-02-01 00:42:51
+sha256sum:
+    008cd7cdcec4904aec424162611fbd7831f55c4a58cde3039707f956b735233e model-00001-of-00003.safetensors
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+    dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055 tokenizer.model

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