---
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: alexredna/Tukan-1.1B-Chat-v0.6
model-index:
- name: Tukan-1.1B-Chat-v0.6_dpo
  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. -->

# Tukan-1.1B-Chat-v0.6_dpo

This model is a fine-tuned version of [alexredna/Tukan-1.1B-Chat-v0.6](https://huggingface.co/alexredna/Tukan-1.1B-Chat-v0.6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6664
- Rewards/chosen: -0.0698
- Rewards/rejected: -0.1297
- Rewards/accuracies: 0.6667
- Rewards/margins: 0.0600
- Logps/rejected: -364.0182
- Logps/chosen: -408.6165
- Logits/rejected: -2.1219
- Logits/chosen: -2.2568

## 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: 3e-07
- train_batch_size: 5
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 32
- total_train_batch_size: 160
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6819        | 0.99  | 61   | 0.6804          | -0.0465        | -0.0746          | 0.6318             | 0.0281          | -363.4672      | -408.3842    | -2.1356         | -2.2671       |
| 0.6718        | 2.0   | 123  | 0.6719          | -0.0689        | -0.1170          | 0.6269             | 0.0482          | -363.8911      | -408.6075    | -2.1242         | -2.2588       |
| 0.6687        | 2.97  | 183  | 0.6664          | -0.0698        | -0.1297          | 0.6667             | 0.0600          | -364.0182      | -408.6165    | -2.1219         | -2.2568       |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16

### Framework versions


- PEFT 0.6.1