oh-mistral-bs4096_lr5.00E-06_schedulercosine_with_min_lr_warmup5.00E-02_minlr5.00E-07
This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the mlfoundations-dev/oh-dcft-v3.1-gpt-4o-mini dataset.
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 256
- gradient_accumulation_steps: 2
- total_train_batch_size: 4096
- total_eval_batch_size: 2048
- 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_with_min_lr
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0a0+b465a5843b.nv24.09
- Datasets 3.0.2
- Tokenizers 0.20.3
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Model tree for mlfoundations-dev/oh-mistral-bs4096_lr5_00E-06_schedulercosine_with_min_lr_warmup5_00E-02_minlr5_00E-07
Base model
mistralai/Mistral-7B-v0.3