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base_model: mistralai/Mistral-Nemo-Instruct-2407
library_name: peft
license: other
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: epidemiology_sft_10000_mcq_2epoch
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. -->
# epidemiology_sft_10000_mcq_2epoch
This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the epidemiology_10000_mcq dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0020
## 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: 10
- eval_batch_size: 10
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 40
- total_eval_batch_size: 40
- 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0042 | 0.1333 | 30 | 0.0041 |
| 0.0039 | 0.2667 | 60 | 0.0039 |
| 0.0039 | 0.4 | 90 | 0.0039 |
| 0.0039 | 0.5333 | 120 | 0.0039 |
| 0.0033 | 0.6667 | 150 | 0.0031 |
| 0.0029 | 0.8 | 180 | 0.0029 |
| 0.0028 | 0.9333 | 210 | 0.0025 |
| 0.0025 | 1.0667 | 240 | 0.0024 |
| 0.0024 | 1.2 | 270 | 0.0024 |
| 0.0027 | 1.3333 | 300 | 0.0024 |
| 0.0025 | 1.4667 | 330 | 0.0023 |
| 0.0023 | 1.6 | 360 | 0.0022 |
| 0.0023 | 1.7333 | 390 | 0.0021 |
| 0.002 | 1.8667 | 420 | 0.0020 |
| 0.0022 | 2.0 | 450 | 0.0020 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1 |