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deepseek-math-7B-finetuned/README.md

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---
library_name: transformers
license: other
base_model: deepseek-ai/deepseek-math-7b-base
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: deepseek-math-lean-sft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deepseek-math-lean-sft
This model is a fine-tuned version of [deepseek-ai/deepseek-math-7b-base](https://huggingface.co/deepseek-ai/deepseek-math-7b-base) on the lean_sft dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0597
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.05
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0744 | 0.1692 | 1000 | 0.0767 |
| 0.068 | 0.3384 | 2000 | 0.0688 |
| 0.0637 | 0.5077 | 3000 | 0.0648 |
| 0.0601 | 0.6769 | 4000 | 0.0620 |
| 0.0608 | 0.8461 | 5000 | 0.0601 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu129
- Datasets 4.0.0
- Tokenizers 0.22.1