---
library_name: transformers
license: llama3
base_model: tsavage68/IE_L3_1000steps_1e6rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: IE_L3_350steps_1e8rate_03beta_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_350steps_1e8rate_03beta_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: 0.6896
- Rewards/chosen: -0.0071
- Rewards/rejected: -0.0198
- Rewards/accuracies: 0.4400
- Rewards/margins: 0.0127
- Logps/rejected: -75.6932
- Logps/chosen: -82.8214
- Logits/rejected: -0.7977
- Logits/chosen: -0.7408

## 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: 350

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6912        | 0.4   | 50   | 0.6940          | -0.0075        | -0.0104          | 0.4000             | 0.0029          | -75.6618       | -82.8226     | -0.7964         | -0.7393       |
| 0.6947        | 0.8   | 100  | 0.6925          | 0.0014         | -0.0057          | 0.3850             | 0.0070          | -75.6461       | -82.7931     | -0.7963         | -0.7394       |
| 0.6881        | 1.2   | 150  | 0.7003          | -0.0102        | -0.0020          | 0.375              | -0.0082         | -75.6340       | -82.8318     | -0.7969         | -0.7398       |
| 0.6776        | 1.6   | 200  | 0.6938          | -0.0057        | -0.0098          | 0.375              | 0.0041          | -75.6601       | -82.8168     | -0.7970         | -0.7399       |
| 0.6859        | 2.0   | 250  | 0.6850          | -0.0033        | -0.0250          | 0.4350             | 0.0217          | -75.7105       | -82.8087     | -0.7975         | -0.7405       |
| 0.7024        | 2.4   | 300  | 0.6893          | -0.0075        | -0.0207          | 0.4400             | 0.0132          | -75.6964       | -82.8228     | -0.7977         | -0.7408       |
| 0.6802        | 2.8   | 350  | 0.6896          | -0.0071        | -0.0198          | 0.4400             | 0.0127          | -75.6932       | -82.8214     | -0.7977         | -0.7408       |


### Framework versions

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