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---
language:
- en
license: other
library_name: transformers
tags:
- generated_from_trainer
base_model:
- Qwen/Qwen2.5-7B-Instruct
datasets:
- Magpie-Align/Magpie-Qwen2.5-Pro-300K-Filtered
license_name: qwen
license_link: https://huggingface.co./Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE
model-index:
- name: cybertron-v4-qw7B-MGS
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 62.64
name: strict accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fblgit/cybertron-v4-qw7B-MGS
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 37.04
name: normalized accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fblgit/cybertron-v4-qw7B-MGS
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 27.72
name: exact match
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fblgit/cybertron-v4-qw7B-MGS
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 8.05
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fblgit/cybertron-v4-qw7B-MGS
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: 13.2
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fblgit/cybertron-v4-qw7B-MGS
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: 38.59
name: accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=fblgit/cybertron-v4-qw7B-MGS
name: Open LLM Leaderboard
---
# cybertron-v4-qw7B-MGS
Introducing: **cybertron-v4** based on Qwen2.5 7B
SFT over Magpie-Align/Magpie-Qwen2.5-Pro-1M-v0.1
## Training procedure
1 Epoch as usual.
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
### Training hyperparameters
The following hyperparameters were used during training:
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7405 | 0.0007 | 1 | 0.5760 |
| 0.6146 | 0.0502 | 71 | 0.5045 |
| 0.5908 | 0.1003 | 142 | 0.4930 |
| 0.5669 | 0.1505 | 213 | 0.4854 |
| 0.5575 | 0.2007 | 284 | 0.4811 |
| 0.535 | 0.2508 | 355 | 0.4765 |
| 0.5161 | 0.3010 | 426 | 0.4736 |
| 0.5268 | 0.3511 | 497 | 0.4726 |
| 0.5119 | 0.4013 | 568 | 0.4701 |
| 0.5329 | 0.4515 | 639 | 0.4687 |
| 0.5167 | 0.5016 | 710 | 0.4673 |
| 0.5105 | 0.5518 | 781 | 0.4660 |
| 0.5203 | 0.6020 | 852 | 0.4653 |
| 0.5035 | 0.6521 | 923 | 0.4646 |
| 0.4903 | 0.7023 | 994 | 0.4641 |
| 0.5031 | 0.7525 | 1065 | 0.4628 |
| 0.5147 | 0.8026 | 1136 | 0.4629 |
| 0.5037 | 0.8528 | 1207 | 0.4620 |
| 0.5029 | 0.9029 | 1278 | 0.4620 |
| 0.492 | 0.9531 | 1349 | 0.4621 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.3.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
# [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/details_fblgit__cybertron-v4-qw7B-MGS)
| Metric |Value|
|-------------------|----:|
|Avg. |31.21|
|IFEval (0-Shot) |62.64|
|BBH (3-Shot) |37.04|
|MATH Lvl 5 (4-Shot)|27.72|
|GPQA (0-shot) | 8.05|
|MuSR (0-shot) |13.20|
|MMLU-PRO (5-shot) |38.59|
|