---
license: apache-2.0
base_model: tsavage68/Hyponatremia_M2_150steps_1e6rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Hyponatremia_M2_400steps_1e8rate_03beta_DPO
  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_400steps_1e8rate_03beta_DPO

This model is a fine-tuned version of [tsavage68/Hyponatremia_M2_150steps_1e6rate_SFT](https://huggingface.co/tsavage68/Hyponatremia_M2_150steps_1e6rate_SFT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6276
- Rewards/chosen: 0.0345
- Rewards/rejected: -0.1027
- Rewards/accuracies: 0.9600
- Rewards/margins: 0.1372
- Logps/rejected: -71.2238
- Logps/chosen: -36.6121
- Logits/rejected: -2.2455
- Logits/chosen: -2.2404

## 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-08
- 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: 400

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.691         | 0.2667 | 50   | 0.6959          | 0.0081         | 0.0125           | 0.4400             | -0.0044         | -70.8398       | -36.7002     | -2.2478         | -2.2427       |
| 0.684         | 0.5333 | 100  | 0.6850          | 0.0066         | -0.0109          | 0.6200             | 0.0175          | -70.9177       | -36.7050     | -2.2462         | -2.2410       |
| 0.6496        | 0.8    | 150  | 0.6433          | 0.0267         | -0.0772          | 0.9000             | 0.1039          | -71.1387       | -36.6380     | -2.2462         | -2.2412       |
| 0.6234        | 1.0667 | 200  | 0.6319          | 0.0320         | -0.0962          | 0.9700             | 0.1281          | -71.2020       | -36.6205     | -2.2465         | -2.2415       |
| 0.6262        | 1.3333 | 250  | 0.6336          | 0.0321         | -0.0927          | 0.9500             | 0.1248          | -71.1904       | -36.6199     | -2.2462         | -2.2411       |
| 0.6215        | 1.6    | 300  | 0.6288          | 0.0386         | -0.0965          | 0.9600             | 0.1352          | -71.2033       | -36.5983     | -2.2455         | -2.2404       |
| 0.6129        | 1.8667 | 350  | 0.6276          | 0.0345         | -0.1027          | 0.9600             | 0.1372          | -71.2238       | -36.6121     | -2.2455         | -2.2404       |
| 0.6301        | 2.1333 | 400  | 0.6276          | 0.0345         | -0.1027          | 0.9600             | 0.1372          | -71.2238       | -36.6121     | -2.2455         | -2.2404       |


### Framework versions

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