generated_from_trainer base_model:dhmeltzer/llama-7b-SFT_ds_wiki65k_1024_r_64_alpha_16_merged region:us
---
base_model: dhmeltzer/llama-7b-SFT_ds_wiki65k_1024_r_64_alpha_16_merged
tags:
- generated_from_trainer
model-index:
- name: llama-7b-SFT-qlora-wiki_DPO_ds_RM_top_2_1024_r_64_alpha_16
  results: []
---

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# llama-7b-SFT-qlora-wiki_DPO_ds_RM_top_2_1024_r_64_alpha_16

This model is a fine-tuned version of [dhmeltzer/llama-7b-SFT_ds_wiki65k_1024_r_64_alpha_16_merged](https://huggingface.co/dhmeltzer/llama-7b-SFT_ds_wiki65k_1024_r_64_alpha_16_merged) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6572
- Rewards/chosen: -0.1473
- Rewards/rejected: -0.2755
- Rewards/accuracies: 0.6128
- Rewards/margins: 0.1282
- Logps/rejected: -203.3539
- Logps/chosen: -207.2538
- Logits/rejected: 1.1534
- Logits/chosen: 1.1690

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6925        | 0.1   | 19   | 0.6761          | -0.1021        | -0.1593          | 0.5697             | 0.0573          | -202.1919      | -206.8013    | 1.1506          | 1.1664        |
| 0.6754        | 0.21  | 38   | 0.6738          | -0.4156        | -0.5460          | 0.5701             | 0.1303          | -206.0580      | -209.9368    | 1.1257          | 1.1406        |
| 0.6799        | 0.31  | 57   | 0.6666          | -0.0458        | -0.1454          | 0.5932             | 0.0996          | -202.0523      | -206.2388    | 1.1176          | 1.1327        |
| 0.6618        | 0.42  | 76   | 0.6637          | -0.1458        | -0.2745          | 0.5971             | 0.1286          | -203.3434      | -207.2391    | 1.1195          | 1.1333        |
| 0.6706        | 0.52  | 95   | 0.6607          | -0.0386        | -0.1827          | 0.5971             | 0.1440          | -202.4252      | -206.1670    | 1.1334          | 1.1484        |
| 0.668         | 0.63  | 114  | 0.6596          | -0.1615        | -0.2945          | 0.6035             | 0.1330          | -203.5434      | -207.3955    | 1.1500          | 1.1661        |
| 0.6712        | 0.73  | 133  | 0.6597          | -0.1703        | -0.2905          | 0.5979             | 0.1202          | -203.5037      | -207.4840    | 1.1515          | 1.1672        |
| 0.6715        | 0.84  | 152  | 0.6588          | -0.1516        | -0.2745          | 0.6100             | 0.1229          | -203.3436      | -207.2964    | 1.1532          | 1.1691        |
| 0.673         | 0.94  | 171  | 0.6572          | -0.1473        | -0.2755          | 0.6128             | 0.1282          | -203.3539      | -207.2538    | 1.1534          | 1.1690        |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
