---
license: mit
base_model: wenbopan/Faro-Yi-9B
tags:
- generated_from_trainer
model-index:
- name: results/Faro-Yi-9B-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. -->

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.0`
```yaml
base_model: wenbopan/Faro-Yi-9B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

is_llama_derived_model: true

load_in_8bit: false
load_in_4bit: false
strict: false

rl: dpo
datasets:
  - path: theIndividual/UltraInteractPair_axolotl
    split: train
    type: chatml

val_set_size: 0.1
output_dir: results/Faro-Yi-9B-DPO

sequence_len: 4096
sample_packing: false
pad_to_sequence_len: false

adapter: lora
lora_model_dir:

lora_r: 16
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_modules_to_save:
lora_fan_in_fan_out:
lora_target_modules:
  - k_proj
  - gate_proj
  - v_proj
  - up_proj
  - q_proj
  - o_proj
  - down_proj

wandb_project: faro-yi-dpo
wandb_entity:
wandb_name:

gradient_accumulation_steps: 1
micro_batch_size: 2
num_epochs: 1
optimizer: paged_adamw_8bit
adam_beta2: 0.95
adam_epsilion: 0.00001
lr_scheduler: linear
learning_rate: 1e-6

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false

gradient_checkpointing: true
gradient_checkpoint_kwargs:
  use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
eval_steps:
eval_table_size:
eval_table_max_new_tokens: 128
save_steps: 45
debug:
deepspeed:
weight_decay: 0.1
special_tokens:
save_safetensors: true

dataloader_num_workers: 16
dataloader_pin_memory: true

```

</details><br>

# results/Faro-Yi-9B-DPO

This model is a fine-tuned version of [wenbopan/Faro-Yi-9B](https://huggingface.co/wenbopan/Faro-Yi-9B) on an unknown dataset.

## 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-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 109761

### Training results



### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.0