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Model: rxavier/Taurus-7B-1.0 Source: Original Platform
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197
README.md
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---
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language:
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- en
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license: mit
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tags:
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- chatml
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- mistral
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- instruct
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- openhermes
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- economics
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datasets:
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- rxavier/economicus
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base_model: teknium/OpenHermes-2.5-Mistral-7B
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model-index:
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- name: Taurus-7B-1.0
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 63.57
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name: normalized accuracy
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
|
||||
- type: acc_norm
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||||
value: 83.64
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||||
name: normalized accuracy
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 63.5
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||||
name: accuracy
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||||
source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 50.21
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source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
|
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value: 78.14
|
||||
name: accuracy
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||||
source:
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
|
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
|
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- type: acc
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value: 59.36
|
||||
name: accuracy
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||||
source:
|
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url: >-
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https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
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name: Open LLM Leaderboard
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library_name: transformers
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---
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# Taurus 7B 1.0
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## Description
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Taurus is an [OpenHermes 2.5](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) finetune using the [Economicus dataset](https://huggingface.co/datasets/rxavier/economicus), an instruct dataset synthetically generated from Economics PhD textbooks.
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The model was trained for 2 epochs (QLoRA) using [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl). The exact config I used can be found [here](https://huggingface.co/rxavier/Taurus-1.0-Mistral-7B/tree/main/axolotl).
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## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_rxavier__Taurus-7B-1.0)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |66.40|
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|AI2 Reasoning Challenge (25-Shot)|63.57|
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|HellaSwag (10-Shot) |83.64|
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|MMLU (5-Shot) |63.50|
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|TruthfulQA (0-shot) |50.21|
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|Winogrande (5-shot) |78.14|
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|GSM8k (5-shot) |59.36|
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## Prompt format
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Taurus uses **ChatML**.
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```
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<|im_start|>system
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System message
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<|im_start|>user
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User message<|im_end|>
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<|im_start|>assistant
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```
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## Usage
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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model_id = "rxavier/Taurus-7B-1.0"
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.bfloat16, #torch.float16 for older GPUs
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device_map="auto", # Requires having accelerate installed, useful in places like Colab with limited VRAM
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)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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generation_config = GenerationConfig(
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bos_token_id=tokenizer.bos_token_id,
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eos_token_id=tokenizer.eos_token_id,
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pad_token_id=tokenizer.pad_token_id,
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)
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system_message = "You are an expert in economics with PhD level knowledge. You are helpful, give thorough and clear explanations, and use equations and formulas where needed."
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prompt = "Give me latex formulas for extended euler equations"
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messages = [{"role": "system",
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"content": system_message},
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{"role": "user",
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"content": prompt}]
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tokens = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to("cuda")
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with torch.no_grad():
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outputs = model.generate(inputs=tokens, generation_config=generation_config, max_length=512)
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print(tokenizer.decode(outputs.cpu().tolist()[0]))
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```
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## GGUF quants
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You can find GGUF quants for llama.cpp [here](https://huggingface.co/rxavier/Taurus-7B-1.0-GGUF).
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4
added_tokens.json
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{
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"<|im_end|>": 32000,
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"<|im_start|>": 32001
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}
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91
axolotl/config.yml
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axolotl/config.yml
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base_model: teknium/OpenHermes-2.5-Mistral-7B
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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is_mistral_derived_model: true
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datasets:
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- path: rxavier/economicus
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type: sharegpt
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conversation: chatml
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#shards: 100
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dataset_prepared_path: taurus/train/last_run_prepared
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val_set_size: 0.05
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sequence_len: 2048
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sample_packing: true
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pad_to_sequence_len: true
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|
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adapter: qlora
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lora_r: 64
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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lora_target_modules:
|
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- q_proj
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- v_proj
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- k_proj
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- o_proj
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- gate_proj
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- down_proj
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- up_proj
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#lora_modules_to_save:
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# - embed_tokens
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# - lm_head
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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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bf16: true
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fp16: false
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tf32: false
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gradient_accumulation_steps: 4
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micro_batch_size: 2
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num_epochs: 2
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optimizer: paged_adamw_8bit
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weight_decay: 0.0
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lr_scheduler: cosine
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learning_rate: 0.0003
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warmup_ratio: 0.03
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adam_beta2: 0.95
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adam_epsilon: 0.00001
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max_grad_norm: 1.0
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|
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gradient_checkpointing: true
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early_stopping_patience:
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|
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evals_per_epoch: 4
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eval_table_size:
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eval_table_max_new_tokens:
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eval_sample_packing: false
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saves_per_epoch: 4
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debug:
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deepspeed:
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fsdp:
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fsdp_config:
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train_on_inputs: false
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group_by_length: false
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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output_dir: taurus/train/output
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save_safetensors: true
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wandb_project: economicus
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wandb_entity:
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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#special_tokens:
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# eos_token: "<|im_end|>"
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#tokens:
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# - "<|im_start|>"
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# - "<|im_end|>"
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chat_template: chatml
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26
config.json
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config.json
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{
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"_name_or_path": "teknium/OpenHermes-2.5-Mistral-7B",
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"architectures": [
|
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"MistralForCausalLM"
|
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],
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"attention_dropout": 0.0,
|
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"bos_token_id": 1,
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"eos_token_id": 32000,
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"hidden_act": "silu",
|
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
|
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"rms_norm_eps": 1e-05,
|
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.39.0.dev0",
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"use_cache": false,
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"vocab_size": 32002
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}
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7
generation_config.json
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"_from_model_config": true,
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"do_sample": true,
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"transformers_version": "4.39.0.dev0"
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}
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"model.layers.31.mlp.gate_proj.weight": "model-00003-of-00003.safetensors",
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00003.safetensors",
|
||||
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|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00003.safetensors",
|
||||
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|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.norm.weight": "model-00003-of-00003.safetensors"
|
||||
}
|
||||
}
|
||||
24
special_tokens_map.json
Normal file
24
special_tokens_map.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "</s>",
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
62
tokenizer_config.json
Normal file
62
tokenizer_config.json
Normal file
@@ -0,0 +1,62 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"add_prefix_space": true,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32000": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32001": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [],
|
||||
"bos_token": "<s>",
|
||||
"chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You are a helpful assistant.' %}{% endif %}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{{'<|im_start|>system\n' + system_message + '<|im_end|>\n'}}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "</s>",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"trust_remote_code": false,
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": true,
|
||||
"use_fast": true
|
||||
}
|
||||
Reference in New Issue
Block a user