sft_5000
This model is a fine-tuned version of mistralai/Mistral-Nemo-Instruct-2407 on the heat_transfer_5000_fs dataset. It achieves the following results on the evaluation set:
- Loss: 0.0013
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: 0.0001
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 24
- total_eval_batch_size: 24
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.009 | 0.1064 | 20 | 0.0042 |
0.0033 | 0.2128 | 40 | 0.0030 |
0.0026 | 0.3191 | 60 | 0.0022 |
0.0025 | 0.4255 | 80 | 0.0019 |
0.0019 | 0.5319 | 100 | 0.0017 |
0.0017 | 0.6383 | 120 | 0.0016 |
0.0016 | 0.7447 | 140 | 0.0014 |
0.0018 | 0.8511 | 160 | 0.0013 |
0.0016 | 0.9574 | 180 | 0.0013 |
Framework versions
- PEFT 0.12.0
- Transformers 4.46.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1
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Model tree for Howard881010/heat_transfer_sft_5000_1epoch_fs
Base model
mistralai/Mistral-Nemo-Base-2407
Finetuned
mistralai/Mistral-Nemo-Instruct-2407