---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Hyponatremia_M2_1000steps_1e7rate_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. -->

# Hyponatremia_M2_1000steps_1e7rate_SFT

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2097

## 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: 1e-07
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.039         | 0.2667 | 50   | 1.9360          |
| 0.7076        | 0.5333 | 100  | 0.5643          |
| 0.2876        | 0.8    | 150  | 0.2857          |
| 0.2565        | 1.0667 | 200  | 0.2616          |
| 0.2355        | 1.3333 | 250  | 0.2328          |
| 0.2188        | 1.6    | 300  | 0.2218          |
| 0.2185        | 1.8667 | 350  | 0.2184          |
| 0.2101        | 2.1333 | 400  | 0.2154          |
| 0.2104        | 2.4    | 450  | 0.2139          |
| 0.2111        | 2.6667 | 500  | 0.2128          |
| 0.2106        | 2.9333 | 550  | 0.2111          |
| 0.2086        | 3.2    | 600  | 0.2106          |
| 0.2078        | 3.4667 | 650  | 0.2101          |
| 0.2027        | 3.7333 | 700  | 0.2101          |
| 0.2049        | 4.0    | 750  | 0.2100          |
| 0.2079        | 4.2667 | 800  | 0.2098          |
| 0.2057        | 4.5333 | 850  | 0.2098          |
| 0.2034        | 4.8    | 900  | 0.2097          |
| 0.205         | 5.0667 | 950  | 0.2097          |
| 0.2045        | 5.3333 | 1000 | 0.2097          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.0.0+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1