add measurement.json

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bespokelabs/Bespoke-Stratos-32B
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: original
+  results: []
+language:
+- en
+datasets:
+- bespokelabs/Bespoke-Stratos-17k
+---
+
+<p align="center">
+    <img src="https://huggingface.co/bespokelabs/Bespoke-MiniCheck-7B/resolve/main/Bespoke-Labs-Logo.png" width="550">
+</p>
+
+## Model description
+This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) on the [Bespoke-Stratos-17k dataset](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k).
+The dataset is derived by distilling DeepSeek-R1 using the data pipeline of Berkeley NovaSky’s Sky-T1 with some modifications. More info in the dataset card at [Bespoke-Stratos-17k](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k).
+It outperforms Qwen-2.5-32B-Instruct on reasoning benchmarks:
+
+| Metric | Bespoke-Stratos-32B | Sky-T1-32B | o1-preview | DeepSeek-R1 | DeepSeek-R1-Distill-Qwen-32B (Ours // Reported)|
+|---|---|---|---|---|---|
+| AIME2024 | 63.3 | 43.3 | 40.0 | 79.8 | 66.7 // 72.6 |
+| MATH500 | 93.0 | 82.4 | 81.4 | 97.3 | 89.8 // 94.3 |
+| GPQA-Diamond | 58.1 | 56.8 | 75.2 | 71.5 | 61.1 // 62.1 |
+| LCB v2 Easy | 96.7 | 86.3 | 92.9 | - | 91.2 // - |
+| LCB v2 Medium | 75.2 | 56.8 | 54.9 | - | 75.7 // - |
+| LCB v2 Hard | 26.2 | 17.9 | 16.3 | - | 38.2 // - |
+| LCB v2 All | 71.1 | 57.9 | 59.1 | - | 72.2 // - |
+
+## Intended uses & limitations
+Apache 2.0 License
+
+
+## Training procedure
+We used 8xH100 to train the model for 27 hours.
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 1
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 12
+- total_train_batch_size: 96
+- total_eval_batch_size: 64
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.46.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3