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_random_1024_r_64_alpha_16
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama-7b-SFT-qlora-wiki_DPO_ds_RM_random_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: 0.6801
- Rewards/chosen: -0.1790
- Rewards/rejected: -0.2369
- Rewards/accuracies: 0.5469
- Rewards/margins: 0.0578
- Logps/rejected: -206.1121
- Logps/chosen: -202.9860
- Logits/rejected: 1.1465
- Logits/chosen: 1.1674

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6904        | 0.1   | 19   | 0.6904          | -0.3143        | -0.3636          | 0.5458             | 0.0493          | -207.3793      | -204.3384    | 1.1224          | 1.1416        |
| 0.6725        | 0.21  | 38   | 0.6850          | -0.3901        | -0.4540          | 0.5547             | 0.0640          | -208.2836      | -205.0964    | 1.1270          | 1.1469        |
| 0.6818        | 0.31  | 57   | 0.6801          | -0.1790        | -0.2369          | 0.5469             | 0.0578          | -206.1121      | -202.9860    | 1.1465          | 1.1674        |
| 0.6671        | 0.41  | 76   | 0.6863          | -0.2598        | -0.3469          | 0.5580             | 0.0871          | -207.2126      | -203.7936    | 1.1468          | 1.1665        |
| 0.6683        | 0.52  | 95   | 0.6841          | -0.1475        | -0.2325          | 0.5502             | 0.0851          | -206.0687      | -202.6704    | 1.1388          | 1.1590        |
| 0.6626        | 0.62  | 114  | 0.6846          | -0.0836        | -0.1600          | 0.5480             | 0.0764          | -205.3429      | -202.0314    | 1.1263          | 1.1474        |
| 0.6593        | 0.72  | 133  | 0.6864          | -0.1272        | -0.2184          | 0.5625             | 0.0912          | -205.9276      | -202.4675    | 1.1106          | 1.1306        |
| 0.672         | 0.83  | 152  | 0.6857          | -0.1452        | -0.2334          | 0.5592             | 0.0882          | -206.0777      | -202.6477    | 1.1086          | 1.1293        |
| 0.6671        | 0.93  | 171  | 0.6855          | -0.1472        | -0.2350          | 0.5547             | 0.0878          | -206.0934      | -202.6673    | 1.1071          | 1.1270        |


### Framework versions

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