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--- |
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base_model: mistralai/Mistral-Nemo-Instruct-2407 |
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library_name: peft |
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license: other |
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tags: |
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- llama-factory |
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- lora |
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- generated_from_trainer |
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model-index: |
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- name: heat_transfer_sft_10000_mcq_a_1epoch |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# heat_transfer_sft_10000_mcq_a_1epoch |
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This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the heat_transfer_10000_mcq_a dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0434 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 20 |
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- total_eval_batch_size: 20 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.0654 | 0.0667 | 30 | 0.0632 | |
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| 0.0595 | 0.1333 | 60 | 0.0577 | |
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| 0.0546 | 0.2 | 90 | 0.0534 | |
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| 0.0555 | 0.2667 | 120 | 0.0530 | |
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| 0.052 | 0.3333 | 150 | 0.0524 | |
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| 0.0529 | 0.4 | 180 | 0.0509 | |
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| 0.0502 | 0.4667 | 210 | 0.0506 | |
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| 0.0479 | 0.5333 | 240 | 0.0487 | |
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| 0.0479 | 0.6 | 270 | 0.0483 | |
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| 0.047 | 0.6667 | 300 | 0.0463 | |
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| 0.0452 | 0.7333 | 330 | 0.0455 | |
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| 0.0437 | 0.8 | 360 | 0.0444 | |
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| 0.0442 | 0.8667 | 390 | 0.0439 | |
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| 0.0439 | 0.9333 | 420 | 0.0434 | |
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| 0.0444 | 1.0 | 450 | 0.0434 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.46.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.1 |
