初始化项目，由ModelHub XC社区提供模型

Model: monsterapi/zephyr-7b-alpha_metamathqa
Source: Original Platform

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README.md

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+---
+library_name: transformers
+tags:
+- meta-math
+- code
+- instruct
+- Zephyr-7B-Alpha
+datasets:
+- meta-math/MetaMathQA
+base_model: HuggingFaceH4/zephyr-7b-alpha
+license: apache-2.0
+---
+
+### Finetuning Overview:
+
+**Model Used:** HuggingFaceH4/zephyr-7b-alpha  
+**Dataset:** meta-math/MetaMathQA  
+
+#### Dataset Insights:
+
+The MetaMathQA dataset is a newly created dataset specifically designed for enhancing the mathematical reasoning capabilities of large language models (LLMs). It is built by bootstrapping mathematical questions and rewriting them from multiple perspectives, providing a comprehensive and challenging environment for LLMs to develop and refine their mathematical problem-solving skills.
+
+#### Finetuning Details:
+
+Using [MonsterAPI](https://monsterapi.ai)'s [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm), this finetuning:
+
+- Was conducted with efficiency and cost-effectiveness in mind.
+- Completed in a total duration of 10.9 hours for 0.5 epoch using an A6000 48GB GPU.
+- Costed `$22.01` for the entire finetuning process.
+
+#### Hyperparameters & Additional Details:
+
+- **Epochs:** 0.5
+- **Total Finetuning Cost:** $22.01
+- **Model Path:** HuggingFaceH4/zephyr-7b-alpha
+- **Learning Rate:** 0.0001
+- **Data Split:** 95% train 5% validation
+- **Gradient Accumulation Steps:** 4
+
+---
+Prompt Structure
+
+```
+Below is an instruction that describes a task. Write a response that appropriately completes the request.  
+
+
+###Instruction:[query]
+
+
+###Response:[response]
+```
+
+---
+### Training loss:
+![training loss](zephyr-mmqa-1.png "Training loss")
+
+
+
+---
+### Benchmark Results:
+
+![GSM8K Accuracy ](benchmark.png "GSM8K Accuracy")
+
+GSM8K is a dataset of 8.5K high quality linguistically diverse grade school math word problems, These problems take between 2 and 8 steps to solve, and solutions primarily involve performing a sequence of elementary calculations using basic arithmetic operations (+ − ×÷) to reach the final answer. A bright middle school student should be able to solve every problem. Its a industry wide used benchmark for testing an LLM for for multi-step mathematical reasoning.
+
+ 
+
+---
+license: apache-2.0

config.json

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+{
+  "_name_or_path": "HuggingFaceH4/zephyr-7b-alpha",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
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+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.35.0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

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+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.35.0"
+}

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+}

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<unk>",
+    "<s>",
+    "</s>"
+  ],
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
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+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
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+  "additional_special_tokens": [
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+    "<s>",
+    "</s>"
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+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n'  + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "truncation_side": "left",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}