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---
license: apache-2.0
datasets:
- agentlans/crash-course
- vicgalle/configurable-system-prompt-multitask
base_model:
- Qwen/Qwen2.5-0.5B-Instruct
model-index:
- name: Qwen2.5-0.5B-Instruct-CrashCourse-dropout
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: wis-k/instruction-following-eval
split: train
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 29.49
name: averaged accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FQwen2.5-0.5B-Instruct-CrashCourse-dropout
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: SaylorTwift/bbh
split: test
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 7.23
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FQwen2.5-0.5B-Instruct-CrashCourse-dropout
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: lighteval/MATH-Hard
split: test
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 0.08
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FQwen2.5-0.5B-Instruct-CrashCourse-dropout
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
split: train
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 1.79
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FQwen2.5-0.5B-Instruct-CrashCourse-dropout
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 1.11
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FQwen2.5-0.5B-Instruct-CrashCourse-dropout
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 6.76
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=agentlans%2FQwen2.5-0.5B-Instruct-CrashCourse-dropout
name: Open LLM Leaderboard
---
# Qwen2.5-0.5B-Instruct-CrashCourse-dropout
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct),
specifically adapted for enhanced performance on instructional and multitask scenarios.
It leverages two datasets: [agentlans/crash-course](https://huggingface.co/datasets/agentlans/crash-course) and
[vicgalle/configurable-system-prompt-multitask](https://huggingface.co/datasets/vicgalle/configurable-system-prompt-multitask)
to improve its capabilities in handling diverse tasks and responding to various instruction formats.
> [!NOTE]
> **Update:** Despite the poor benchmark, the model seems OK at slightly complex prompts. There's more finetuning potential here.
## Intended Use
This model is designed for:
- Answering questions related to crash course materials
- Handling configurable system prompts for multitask scenarios
- General instruction-following tasks
## Training Procedure
The model was fine-tuned on the specified datasets using the Qwen2.5-0.5B-Instruct as the base model.
More details on the training process will be added here later.
## Limitations
- The model's performance may be biased towards the specific domains covered in the training datasets.
- As with all language models, it may occasionally produce inaccurate or inconsistent outputs.
- The model's knowledge is limited to the information available in its training data and the base model's knowledge cutoff.
## Ethical Considerations
Users should be aware that this model, like all AI models, may reflect biases present in its training data. It's crucial to use the model responsibly and to verify important information from authoritative sources.
## Additional Information
For more details on the base model, please refer to the Qwen/Qwen2.5-0.5B-Instruct model card. For information about the datasets used in fine-tuning, check the respective dataset cards on the Hugging Face Hub.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/agentlans__Qwen2.5-0.5B-Instruct-CrashCourse-dropout-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=agentlans%2FQwen2.5-0.5B-Instruct-CrashCourse-dropout&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
| Metric | Qwen2.5-0.5B-Instruct-CrashCourse-dropout | Qwen2.5-0.5B-Instruct |
|-------------------|-----------------------------------------:|----------------------:|
| **Average** | 7.74 % | 8.38 % |
| IFEval (0-Shot) | 29.49 % | 31.53 % |
| BBH (3-Shot) | 7.23 % | 8.17 % |
| MATH Lvl 5 (4-Shot)| 0.08 % | 0.00 % |
| GPQA (0-shot) | 1.79 % | 1.23 % |
| MuSR (0-shot) | 1.11 % | 1.37 % |
| MMLU-PRO (5-shot) | 6.76 % | 8.00 % |
|