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Model: qnguyen3/Master-Yi-9B Source: Original Platform
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---
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license: apache-2.0
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---
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## Model Description
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Master is a collection of LLMs trained using human-collected seed questions and regenerate the answers with a mixture of high performance Open-source LLMs.
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**Master-Yi-9B** is trained using the ORPO technique. The model shows strong abilities in reasoning on coding and math questions.
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**Quantized Version**: [Here](https://huggingface.co/qnguyen3/Master-Yi-9B-GGUF)
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**Communitiy Quantization** (Thanks to [@LoneStriker](https://huggingface.co/LoneStriker))
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- exl2: [Master-Yi-9B-8.0bpw-h8-exl2](https://huggingface.co/LoneStriker/Master-Yi-9B-8.0bpw-h8-exl2), [Master-Yi-9B-6.0bpw-h6-exl2](https://huggingface.co/LoneStriker/Master-Yi-9B-6.0bpw-h6-exl2), [Master-Yi-9B-5.0bpw-h6-exl2](https://huggingface.co/LoneStriker/Master-Yi-9B-5.0bpw-h6-exl2), [Master-Yi-9B-4.0bpw-h6-exl2](https://huggingface.co/LoneStriker/Master-Yi-9B-4.0bpw-h6-exl2)
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- GGUFs: [Master-Yi-9B-GGUF](https://huggingface.co/LoneStriker/Master-Yi-9B-GGUF)
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**Master-Yi-9B-Vision**: **Coming Soon**
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## Prompt Template
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```
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<|im_start|>system
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You are a helpful AI assistant.<|im_end|>
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<|im_start|>user
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What is the meaning of life?<|im_end|>
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<|im_start|>assistant
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```
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## Examples
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## Inference Code
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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device = "cuda" # the device to load the model onto
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model = AutoModelForCausalLM.from_pretrained(
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"qnguyen3/Master-Yi-9B",
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torch_dtype='auto',
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained("qnguyen3/Master-Yi-9B")
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prompt = "What is the mearning of life?"
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messages = [
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{"role": "system", "content": "You are a helpful AI assistant."},
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(device)
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generated_ids = model.generate(
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model_inputs.input_ids,
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max_new_tokens=1024,
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eos_token_id=tokenizer.eos_token_id,
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temperature=0.25,
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)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids)[0]
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print(response)
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```
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## Benchmarks
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### Nous Benchmark:
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| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
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|---------------------------------------------------|------:|------:|---------:|-------:|------:|
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|[Master-Yi-9B](https://huggingface.co/qnguyen3/Master-Yi-9B)| 43.55| 71.48| 48.54| 41.43| 51.25|
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### AGIEval
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```
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| Task |Version| Metric |Value| |Stderr|
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|------------------------------|------:|--------|----:|---|-----:|
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|agieval_aqua_rat | 0|acc |35.83|± | 3.01|
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| | |acc_norm|31.89|± | 2.93|
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|agieval_logiqa_en | 0|acc |38.25|± | 1.91|
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| | |acc_norm|37.79|± | 1.90|
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|agieval_lsat_ar | 0|acc |23.04|± | 2.78|
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| | |acc_norm|20.43|± | 2.66|
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|agieval_lsat_lr | 0|acc |48.04|± | 2.21|
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| | |acc_norm|42.75|± | 2.19|
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|agieval_lsat_rc | 0|acc |61.34|± | 2.97|
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| | |acc_norm|52.79|± | 3.05|
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|agieval_sat_en | 0|acc |79.13|± | 2.84|
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| | |acc_norm|72.33|± | 3.12|
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|agieval_sat_en_without_passage| 0|acc |44.17|± | 3.47|
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| | |acc_norm|42.72|± | 3.45|
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|agieval_sat_math | 0|acc |52.27|± | 3.38|
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| | |acc_norm|47.73|± | 3.38|
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Average: 43.55%
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```
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### GPT4All
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```
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| Task |Version| Metric |Value| |Stderr|
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|-------------|------:|--------|----:|---|-----:|
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|arc_challenge| 0|acc |54.95|± | 1.45|
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| | |acc_norm|58.70|± | 1.44|
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|arc_easy | 0|acc |82.28|± | 0.78|
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| | |acc_norm|81.10|± | 0.80|
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|boolq | 1|acc |86.15|± | 0.60|
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|hellaswag | 0|acc |59.16|± | 0.49|
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| | |acc_norm|77.53|± | 0.42|
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|openbookqa | 0|acc |37.40|± | 2.17|
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| | |acc_norm|44.00|± | 2.22|
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|piqa | 0|acc |79.00|± | 0.95|
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| | |acc_norm|80.25|± | 0.93|
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|winogrande | 0|acc |72.61|± | 1.25|
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Average: 71.48%
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```
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### TruthfulQA
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```
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| Task |Version|Metric|Value| |Stderr|
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|-------------|------:|------|----:|---|-----:|
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|truthfulqa_mc| 1|mc1 |33.05|± | 1.65|
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| | |mc2 |48.54|± | 1.54|
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Average: 48.54%
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```
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### Bigbench
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```
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| Task |Version| Metric |Value| |Stderr|
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|------------------------------------------------|------:|---------------------|----:|---|-----:|
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|bigbench_causal_judgement | 0|multiple_choice_grade|54.74|± | 3.62|
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|bigbench_date_understanding | 0|multiple_choice_grade|68.02|± | 2.43|
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|bigbench_disambiguation_qa | 0|multiple_choice_grade|40.31|± | 3.06|
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|bigbench_geometric_shapes | 0|multiple_choice_grade|30.36|± | 2.43|
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| | |exact_str_match | 2.23|± | 0.78|
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|bigbench_logical_deduction_five_objects | 0|multiple_choice_grade|26.00|± | 1.96|
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|bigbench_logical_deduction_seven_objects | 0|multiple_choice_grade|20.71|± | 1.53|
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|bigbench_logical_deduction_three_objects | 0|multiple_choice_grade|44.00|± | 2.87|
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|bigbench_movie_recommendation | 0|multiple_choice_grade|35.00|± | 2.14|
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|bigbench_navigate | 0|multiple_choice_grade|58.40|± | 1.56|
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|bigbench_reasoning_about_colored_objects | 0|multiple_choice_grade|61.80|± | 1.09|
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|bigbench_ruin_names | 0|multiple_choice_grade|42.41|± | 2.34|
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|bigbench_salient_translation_error_detection | 0|multiple_choice_grade|31.56|± | 1.47|
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|bigbench_snarks | 0|multiple_choice_grade|55.25|± | 3.71|
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|bigbench_sports_understanding | 0|multiple_choice_grade|69.37|± | 1.47|
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|bigbench_temporal_sequences | 0|multiple_choice_grade|27.70|± | 1.42|
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|bigbench_tracking_shuffled_objects_five_objects | 0|multiple_choice_grade|21.36|± | 1.16|
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|bigbench_tracking_shuffled_objects_seven_objects| 0|multiple_choice_grade|14.69|± | 0.85|
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|bigbench_tracking_shuffled_objects_three_objects| 0|multiple_choice_grade|44.00|± | 2.87|
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Average: 41.43%
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```
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**Average score**: 51.25%
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### OpenLLM Benchmark:
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| Model |ARC |HellaSwag|MMLU |TruthfulQA|Winogrande|GSM8K|Average|
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|---------------------------------------------------|---:|--------:|----:|---------:|---------:|----:|------:|
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|[Master-Yi-9B](https://huggingface.co/qnguyen3/Master-Yi-9B)|61.6| 79.89|69.95| 48.59| 77.35|67.48| 67.48|
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### ARC
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```
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| Task |Version| Metric | Value | |Stderr|
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|-------------|------:|--------------------|-------------|---|------|
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|arc_challenge| 1|acc,none | 0.59| | |
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| | |acc_stderr,none | 0.01| | |
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| | |acc_norm,none | 0.62| | |
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| | |acc_norm_stderr,none| 0.01| | |
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| | |alias |arc_challenge| | |
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Average: 61.6%
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```
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### HellaSwag
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```
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| Task |Version| Metric | Value | |Stderr|
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|---------|------:|--------------------|---------|---|------|
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|hellaswag| 1|acc,none | 0.61| | |
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| | |acc_stderr,none | 0| | |
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| | |acc_norm,none | 0.80| | |
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| | |acc_norm_stderr,none| 0| | |
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| | |alias |hellaswag| | |
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Average: 79.89%
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```
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### MMLU
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```
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| Task |Version| Metric | Value | |Stderr|
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|----------------------------------------|-------|---------------|---------------------------------------|---|------|
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|mmlu |N/A |acc,none | 0.7| | |
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| | |acc_stderr,none| 0| | |
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| | |alias |mmlu | | |
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|mmlu_abstract_algebra | 0|alias | - abstract_algebra | | |
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| | |acc,none |0.46 | | |
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| | |acc_stderr,none|0.05 | | |
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|mmlu_anatomy | 0|alias | - anatomy | | |
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| | |acc,none |0.64 | | |
|
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| | |acc_stderr,none|0.04 | | |
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|mmlu_astronomy | 0|alias | - astronomy | | |
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| | |acc,none |0.77 | | |
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| | |acc_stderr,none|0.03 | | |
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|mmlu_business_ethics | 0|alias | - business_ethics | | |
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| | |acc,none |0.76 | | |
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| | |acc_stderr,none|0.04 | | |
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|mmlu_clinical_knowledge | 0|alias | - clinical_knowledge | | |
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| | |acc,none |0.71 | | |
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| | |acc_stderr,none|0.03 | | |
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|mmlu_college_biology | 0|alias | - college_biology | | |
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| | |acc,none |0.82 | | |
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| | |acc_stderr,none|0.03 | | |
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|mmlu_college_chemistry | 0|alias | - college_chemistry | | |
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| | |acc,none |0.52 | | |
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| | |acc_stderr,none|0.05 | | |
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|mmlu_college_computer_science | 0|alias | - college_computer_science | | |
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| | |acc,none |0.56 | | |
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| | |acc_stderr,none|0.05 | | |
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|mmlu_college_mathematics | 0|alias | - college_mathematics | | |
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| | |acc,none |0.44 | | |
|
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| | |acc_stderr,none|0.05 | | |
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|mmlu_college_medicine | 0|alias | - college_medicine | | |
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| | |acc,none |0.72 | | |
|
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| | |acc_stderr,none|0.03 | | |
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|mmlu_college_physics | 0|alias | - college_physics | | |
|
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| | |acc,none |0.45 | | |
|
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| | |acc_stderr,none|0.05 | | |
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|mmlu_computer_security | 0|alias | - computer_security | | |
|
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| | |acc,none |0.81 | | |
|
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| | |acc_stderr,none|0.04 | | |
|
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|mmlu_conceptual_physics | 0|alias | - conceptual_physics | | |
|
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| | |acc,none |0.74 | | |
|
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| | |acc_stderr,none|0.03 | | |
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|mmlu_econometrics | 0|alias | - econometrics | | |
|
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| | |acc,none |0.65 | | |
|
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| | |acc_stderr,none|0.04 | | |
|
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|mmlu_electrical_engineering | 0|alias | - electrical_engineering | | |
|
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| | |acc,none |0.72 | | |
|
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| | |acc_stderr,none|0.04 | | |
|
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|mmlu_elementary_mathematics | 0|alias | - elementary_mathematics | | |
|
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| | |acc,none |0.62 | | |
|
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| | |acc_stderr,none|0.02 | | |
|
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|mmlu_formal_logic | 0|alias | - formal_logic | | |
|
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| | |acc,none |0.57 | | |
|
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| | |acc_stderr,none|0.04 | | |
|
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|mmlu_global_facts | 0|alias | - global_facts | | |
|
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| | |acc,none |0.46 | | |
|
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| | |acc_stderr,none|0.05 | | |
|
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|mmlu_high_school_biology | 0|alias | - high_school_biology | | |
|
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| | |acc,none |0.86 | | |
|
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| | |acc_stderr,none|0.02 | | |
|
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|mmlu_high_school_chemistry | 0|alias | - high_school_chemistry | | |
|
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| | |acc,none |0.67 | | |
|
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| | |acc_stderr,none|0.03 | | |
|
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|mmlu_high_school_computer_science | 0|alias | - high_school_computer_science | | |
|
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| | |acc,none |0.84 | | |
|
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| | |acc_stderr,none|0.04 | | |
|
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|mmlu_high_school_european_history | 0|alias | - high_school_european_history | | |
|
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| | |acc,none |0.82 | | |
|
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| | |acc_stderr,none|0.03 | | |
|
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|mmlu_high_school_geography | 0|alias | - high_school_geography | | |
|
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| | |acc,none |0.86 | | |
|
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| | |acc_stderr,none|0.02 | | |
|
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|mmlu_high_school_government_and_politics| 0|alias | - high_school_government_and_politics| | |
|
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| | |acc,none |0.90 | | |
|
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| | |acc_stderr,none|0.02 | | |
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|mmlu_high_school_macroeconomics | 0|alias | - high_school_macroeconomics | | |
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| | |acc,none |0.75 | | |
|
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| | |acc_stderr,none|0.02 | | |
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|mmlu_high_school_mathematics | 0|alias | - high_school_mathematics | | |
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| | |acc,none |0.43 | | |
|
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| | |acc_stderr,none|0.03 | | |
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|mmlu_high_school_microeconomics | 0|alias | - high_school_microeconomics | | |
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| | |acc,none |0.86 | | |
|
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| | |acc_stderr,none|0.02 | | |
|
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|mmlu_high_school_physics | 0|alias | - high_school_physics | | |
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| | |acc,none |0.45 | | |
|
||||
| | |acc_stderr,none|0.04 | | |
|
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|mmlu_high_school_psychology | 0|alias | - high_school_psychology | | |
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| | |acc,none |0.87 | | |
|
||||
| | |acc_stderr,none|0.01 | | |
|
||||
|mmlu_high_school_statistics | 0|alias | - high_school_statistics | | |
|
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| | |acc,none |0.68 | | |
|
||||
| | |acc_stderr,none|0.03 | | |
|
||||
|mmlu_high_school_us_history | 0|alias | - high_school_us_history | | |
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| | |acc,none |0.85 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_high_school_world_history | 0|alias | - high_school_world_history | | |
|
||||
| | |acc,none |0.85 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_human_aging | 0|alias | - human_aging | | |
|
||||
| | |acc,none |0.76 | | |
|
||||
| | |acc_stderr,none|0.03 | | |
|
||||
|mmlu_human_sexuality | 0|alias | - human_sexuality | | |
|
||||
| | |acc,none |0.78 | | |
|
||||
| | |acc_stderr,none|0.04 | | |
|
||||
|mmlu_humanities |N/A |alias | - humanities | | |
|
||||
| | |acc,none |0.63 | | |
|
||||
| | |acc_stderr,none|0.01 | | |
|
||||
|mmlu_international_law | 0|alias | - international_law | | |
|
||||
| | |acc,none |0.79 | | |
|
||||
| | |acc_stderr,none|0.04 | | |
|
||||
|mmlu_jurisprudence | 0|alias | - jurisprudence | | |
|
||||
| | |acc,none |0.79 | | |
|
||||
| | |acc_stderr,none|0.04 | | |
|
||||
|mmlu_logical_fallacies | 0|alias | - logical_fallacies | | |
|
||||
| | |acc,none |0.80 | | |
|
||||
| | |acc_stderr,none|0.03 | | |
|
||||
|mmlu_machine_learning | 0|alias | - machine_learning | | |
|
||||
| | |acc,none |0.52 | | |
|
||||
| | |acc_stderr,none|0.05 | | |
|
||||
|mmlu_management | 0|alias | - management | | |
|
||||
| | |acc,none |0.83 | | |
|
||||
| | |acc_stderr,none|0.04 | | |
|
||||
|mmlu_marketing | 0|alias | - marketing | | |
|
||||
| | |acc,none |0.89 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_medical_genetics | 0|alias | - medical_genetics | | |
|
||||
| | |acc,none |0.78 | | |
|
||||
| | |acc_stderr,none|0.04 | | |
|
||||
|mmlu_miscellaneous | 0|alias | - miscellaneous | | |
|
||||
| | |acc,none |0.85 | | |
|
||||
| | |acc_stderr,none|0.01 | | |
|
||||
|mmlu_moral_disputes | 0|alias | - moral_disputes | | |
|
||||
| | |acc,none |0.75 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_moral_scenarios | 0|alias | - moral_scenarios | | |
|
||||
| | |acc,none |0.48 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_nutrition | 0|alias | - nutrition | | |
|
||||
| | |acc,none |0.77 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_other |N/A |alias | - other | | |
|
||||
| | |acc,none |0.75 | | |
|
||||
| | |acc_stderr,none|0.01 | | |
|
||||
|mmlu_philosophy | 0|alias | - philosophy | | |
|
||||
| | |acc,none |0.78 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_prehistory | 0|alias | - prehistory | | |
|
||||
| | |acc,none |0.77 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_professional_accounting | 0|alias | - professional_accounting | | |
|
||||
| | |acc,none |0.57 | | |
|
||||
| | |acc_stderr,none|0.03 | | |
|
||||
|mmlu_professional_law | 0|alias | - professional_law | | |
|
||||
| | |acc,none |0.50 | | |
|
||||
| | |acc_stderr,none|0.01 | | |
|
||||
|mmlu_professional_medicine | 0|alias | - professional_medicine | | |
|
||||
| | |acc,none |0.71 | | |
|
||||
| | |acc_stderr,none|0.03 | | |
|
||||
|mmlu_professional_psychology | 0|alias | - professional_psychology | | |
|
||||
| | |acc,none |0.73 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_public_relations | 0|alias | - public_relations | | |
|
||||
| | |acc,none |0.76 | | |
|
||||
| | |acc_stderr,none|0.04 | | |
|
||||
|mmlu_security_studies | 0|alias | - security_studies | | |
|
||||
| | |acc,none |0.78 | | |
|
||||
| | |acc_stderr,none|0.03 | | |
|
||||
|mmlu_social_sciences |N/A |alias | - social_sciences | | |
|
||||
| | |acc,none |0.81 | | |
|
||||
| | |acc_stderr,none|0.01 | | |
|
||||
|mmlu_sociology | 0|alias | - sociology | | |
|
||||
| | |acc,none |0.86 | | |
|
||||
| | |acc_stderr,none|0.02 | | |
|
||||
|mmlu_stem |N/A |alias | - stem | | |
|
||||
| | |acc,none |0.65 | | |
|
||||
| | |acc_stderr,none|0.01 | | |
|
||||
|mmlu_us_foreign_policy | 0|alias | - us_foreign_policy | | |
|
||||
| | |acc,none |0.92 | | |
|
||||
| | |acc_stderr,none|0.03 | | |
|
||||
|mmlu_virology | 0|alias | - virology | | |
|
||||
| | |acc,none |0.58 | | |
|
||||
| | |acc_stderr,none|0.04 | | |
|
||||
|mmlu_world_religions | 0|alias | - world_religions | | |
|
||||
| | |acc,none |0.82 | | |
|
||||
| | |acc_stderr,none|0.03 | | |
|
||||
|
||||
Average: 69.95%
|
||||
```
|
||||
|
||||
### TruthfulQA
|
||||
```
|
||||
| Task |Version| Metric | Value | |Stderr|
|
||||
|--------------|-------|-----------------------|-----------------|---|------|
|
||||
|truthfulqa |N/A |bleu_acc,none | 0.45| | |
|
||||
| | |bleu_acc_stderr,none | 0.02| | |
|
||||
| | |rouge1_acc,none | 0.45| | |
|
||||
| | |rouge1_acc_stderr,none | 0.02| | |
|
||||
| | |rouge2_diff,none | 0.92| | |
|
||||
| | |rouge2_diff_stderr,none| 1.07| | |
|
||||
| | |bleu_max,none | 23.77| | |
|
||||
| | |bleu_max_stderr,none | 0.81| | |
|
||||
| | |rouge2_acc,none | 0.38| | |
|
||||
| | |rouge2_acc_stderr,none | 0.02| | |
|
||||
| | |acc,none | 0.41| | |
|
||||
| | |acc_stderr,none | 0.01| | |
|
||||
| | |rougeL_diff,none | 1.57| | |
|
||||
| | |rougeL_diff_stderr,none| 0.93| | |
|
||||
| | |rougeL_acc,none | 0.46| | |
|
||||
| | |rougeL_acc_stderr,none | 0.02| | |
|
||||
| | |bleu_diff,none | 1.38| | |
|
||||
| | |bleu_diff_stderr,none | 0.75| | |
|
||||
| | |rouge2_max,none | 33.01| | |
|
||||
| | |rouge2_max_stderr,none | 1.05| | |
|
||||
| | |rouge1_diff,none | 1.72| | |
|
||||
| | |rouge1_diff_stderr,none| 0.92| | |
|
||||
| | |rougeL_max,none | 45.25| | |
|
||||
| | |rougeL_max_stderr,none | 0.92| | |
|
||||
| | |rouge1_max,none | 48.29| | |
|
||||
| | |rouge1_max_stderr,none | 0.90| | |
|
||||
| | |alias |truthfulqa | | |
|
||||
|truthfulqa_gen| 3|bleu_max,none | 23.77| | |
|
||||
| | |bleu_max_stderr,none | 0.81| | |
|
||||
| | |bleu_acc,none | 0.45| | |
|
||||
| | |bleu_acc_stderr,none | 0.02| | |
|
||||
| | |bleu_diff,none | 1.38| | |
|
||||
| | |bleu_diff_stderr,none | 0.75| | |
|
||||
| | |rouge1_max,none | 48.29| | |
|
||||
| | |rouge1_max_stderr,none | 0.90| | |
|
||||
| | |rouge1_acc,none | 0.45| | |
|
||||
| | |rouge1_acc_stderr,none | 0.02| | |
|
||||
| | |rouge1_diff,none | 1.72| | |
|
||||
| | |rouge1_diff_stderr,none| 0.92| | |
|
||||
| | |rouge2_max,none | 33.01| | |
|
||||
| | |rouge2_max_stderr,none | 1.05| | |
|
||||
| | |rouge2_acc,none | 0.38| | |
|
||||
| | |rouge2_acc_stderr,none | 0.02| | |
|
||||
| | |rouge2_diff,none | 0.92| | |
|
||||
| | |rouge2_diff_stderr,none| 1.07| | |
|
||||
| | |rougeL_max,none | 45.25| | |
|
||||
| | |rougeL_max_stderr,none | 0.92| | |
|
||||
| | |rougeL_acc,none | 0.46| | |
|
||||
| | |rougeL_acc_stderr,none | 0.02| | |
|
||||
| | |rougeL_diff,none | 1.57| | |
|
||||
| | |rougeL_diff_stderr,none| 0.93| | |
|
||||
| | |alias | - truthfulqa_gen| | |
|
||||
|truthfulqa_mc1| 2|acc,none | 0.33| | |
|
||||
| | |acc_stderr,none | 0.02| | |
|
||||
| | |alias | - truthfulqa_mc1| | |
|
||||
|truthfulqa_mc2| 2|acc,none | 0.49| | |
|
||||
| | |acc_stderr,none | 0.02| | |
|
||||
| | |alias | - truthfulqa_mc2| | |
|
||||
|
||||
Average: 48.59%
|
||||
```
|
||||
|
||||
### Winogrande
|
||||
```
|
||||
| Task |Version| Metric | Value | |Stderr|
|
||||
|----------|------:|---------------|----------|---|------|
|
||||
|winogrande| 1|acc,none | 0.77| | |
|
||||
| | |acc_stderr,none| 0.01| | |
|
||||
| | |alias |winogrande| | |
|
||||
|
||||
Average: 77.35%
|
||||
```
|
||||
|
||||
### GSM8K
|
||||
```
|
||||
|Task |Version| Metric |Value| |Stderr|
|
||||
|-----|------:|-----------------------------------|-----|---|------|
|
||||
|gsm8k| 3|exact_match,strict-match | 0.67| | |
|
||||
| | |exact_match_stderr,strict-match | 0.01| | |
|
||||
| | |exact_match,flexible-extract | 0.68| | |
|
||||
| | |exact_match_stderr,flexible-extract| 0.01| | |
|
||||
| | |alias |gsm8k| | |
|
||||
|
||||
Average: 67.48%
|
||||
```
|
||||
|
||||
**Average score**: 67.48%
|
||||
29
config.json
Normal file
29
config.json
Normal file
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"_name_or_path": "01-ai/Yi-1.5-9B",
|
||||
"architectures": [
|
||||
"LlamaForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
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"attention_dropout": 0.0,
|
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"bos_token_id": 1,
|
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"eos_token_id": 7,
|
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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": 11008,
|
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|
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"model_type": "llama",
|
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|
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|
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"num_key_value_heads": 4,
|
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"pad_token_id": 0,
|
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"pretraining_tp": 1,
|
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"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 5000000.0,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.40.1",
|
||||
"use_cache": false,
|
||||
"vocab_size": 64000
|
||||
}
|
||||
7
generation_config.json
Normal file
7
generation_config.json
Normal file
@@ -0,0 +1,7 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 1,
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}
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442
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Normal file
442
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Normal file
@@ -0,0 +1,442 @@
|
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|
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39
special_tokens_map.json
Normal file
39
special_tokens_map.json
Normal file
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|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
174152
tokenizer.json
Normal file
174152
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:386c49cf943d71aa110361135338c50e38beeff0a66593480421f37b319e1a39
|
||||
size 1033105
|
||||
62
tokenizer_config.json
Normal file
62
tokenizer_config.json
Normal file
@@ -0,0 +1,62 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_eos_token": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<|startoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"6": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"7": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>"
|
||||
],
|
||||
"bos_token": "<|startoftext|>",
|
||||
"chat_template": "{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ '<|im_start|>system\\n' + system_message + '<|im_end|>\\n' }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|im_start|>user\\n' + content + '<|im_end|>\\n<|im_start|>assistant\\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<|im_end|>' + '\\n' }}{% endif %}{% endfor %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"legacy": true,
|
||||
"model_max_length": 4096,
|
||||
"pad_token": "<unk>",
|
||||
"padding_side": "right",
|
||||
"sp_model_kwargs": {},
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
70503
trainer_state.json
Normal file
70503
trainer_state.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user