---
library_name: transformers
license: llama3
base_model: tsavage68/IE_L3_1000steps_1e6rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: IE_L3_100steps_1e7rate_05beta_cSFTDPO
  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. -->

# IE_L3_100steps_1e7rate_05beta_cSFTDPO

This model is a fine-tuned version of [tsavage68/IE_L3_1000steps_1e6rate_SFT](https://huggingface.co/tsavage68/IE_L3_1000steps_1e6rate_SFT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1803
- Rewards/chosen: -0.7835
- Rewards/rejected: -7.7662
- Rewards/accuracies: 0.7400
- Rewards/margins: 6.9827
- Logps/rejected: -91.1596
- Logps/chosen: -84.3647
- Logits/rejected: -0.7936
- Logits/chosen: -0.7251

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4416        | 0.4   | 50   | 0.3457          | -0.0969        | -1.1506          | 0.7400             | 1.0537          | -77.9284       | -82.9916     | -0.7954         | -0.7373       |
| 0.1388        | 0.8   | 100  | 0.1803          | -0.7835        | -7.7662          | 0.7400             | 6.9827          | -91.1596       | -84.3647     | -0.7936         | -0.7251       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1