generated_from_trainer base_model:dhmeltzer/llama-7b-SFT_eli5_wiki65k_1024_r_64_alpha_16_merged region:us
---
base_model: dhmeltzer/llama-7b-SFT_eli5_wiki65k_1024_r_64_alpha_16_merged
tags:
- generated_from_trainer
model-index:
- name: llama-7b-SFT-qlora-eli5-wiki_DPO_ds_RM_random_1024_r_64_alpha_16
  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. -->

# llama-7b-SFT-qlora-eli5-wiki_DPO_ds_RM_random_1024_r_64_alpha_16

This model is a fine-tuned version of [dhmeltzer/llama-7b-SFT_eli5_wiki65k_1024_r_64_alpha_16_merged](https://huggingface.co/dhmeltzer/llama-7b-SFT_eli5_wiki65k_1024_r_64_alpha_16_merged) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6788
- Rewards/chosen: -0.0760
- Rewards/rejected: -0.1428
- Rewards/accuracies: 0.5781
- Rewards/margins: 0.0669
- Logps/rejected: -202.0682
- Logps/chosen: -199.2469
- Logits/rejected: 1.0323
- Logits/chosen: 1.0541

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6913        | 0.1   | 19   | 0.6845          | -0.4006        | -0.4672          | 0.5558             | 0.0665          | -205.3114      | -202.4936    | 1.0265          | 1.0467        |
| 0.6768        | 0.21  | 38   | 0.6796          | -0.3409        | -0.4196          | 0.5603             | 0.0787          | -204.8360      | -201.8965    | 1.0326          | 1.0538        |
| 0.6771        | 0.31  | 57   | 0.6788          | -0.0760        | -0.1428          | 0.5781             | 0.0669          | -202.0682      | -199.2469    | 1.0323          | 1.0541        |
| 0.6665        | 0.41  | 76   | 0.6826          | -0.1511        | -0.2355          | 0.5703             | 0.0843          | -202.9944      | -199.9986    | 1.0413          | 1.0635        |
| 0.6669        | 0.52  | 95   | 0.6830          | -0.1285        | -0.2165          | 0.5781             | 0.0880          | -202.8050      | -199.7720    | 1.0299          | 1.0522        |
| 0.669         | 0.62  | 114  | 0.6800          | -0.0932        | -0.1803          | 0.5725             | 0.0871          | -202.4429      | -199.4187    | 1.0126          | 1.0352        |
| 0.6559        | 0.72  | 133  | 0.6829          | -0.0011        | -0.1074          | 0.5759             | 0.1063          | -201.7135      | -198.4980    | 1.0015          | 1.0232        |
| 0.6698        | 0.83  | 152  | 0.6810          | -0.0519        | -0.1530          | 0.5781             | 0.1011          | -202.1696      | -199.0062    | 0.9974          | 1.0192        |
| 0.6643        | 0.93  | 171  | 0.6799          | -0.0579        | -0.1589          | 0.5658             | 0.1010          | -202.2284      | -199.0658    | 1.0002          | 1.0220        |


### Framework versions

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