transformers safetensors deci generated_from_trainer custom_code dataset:HuggingFaceH4/ultrachat_200k dataset:HuggingFaceH4/ultrafeedback_binarized base_model:Deci/DeciLM-7B license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: Deci/DeciLM-7B
tags:
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: bbdeci7b-sft-lora-dpo-lora
  results: []
---

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# bbdeci7b-sft-lora-dpo-lora

This model is a SFT then DPO fine-tuned version of [Deci/DeciLM-7B](https://huggingface.co/Deci/DeciLM-7B) on the [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k) for SFT 
and the [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized)

Evals and more details coming soon


SFT was conducted on  2X Nvidia A100 for 21 Hours, and DPO was codnucted on 8X Nvida A100 for 4 Hours

It achieves the following results on the evaluation set(SFT):
- Loss: 1.0110

It achieves the following results on the evaluation set(DPO):
- Loss: 0.5908
- Rewards/chosen: 0.0960
- Rewards/rejected: -0.2480
- Rewards/accuracies: 0.7222
- Rewards/margins: 0.3440
- Logps/rejected: -241.9212
- Logps/chosen: -295.2642
- Logits/rejected: -2.6769
- Logits/chosen: -2.6941



### Training hyperparameters


The following hyperparameters were used during SFT training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 128
- total_train_batch_size: 1024
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1


The following hyperparameters were used during DPO training:
- learning_rate: 5e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- total_eval_batch_size: 32
- 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

SFT:

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0062        | 1.00  | 136  | 1.0110          |

DPO:

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6401        | 1.0   | 121  | 0.6354          | 0.0634         | -0.0940          | 0.7302             | 0.1573          | -240.3806      | -295.5903    | -2.6840         | -2.7020       |
| 0.6014        | 2.0   | 242  | 0.5988          | 0.0861         | -0.2096          | 0.7460             | 0.2956          | -241.5365      | -295.3633    | -2.6795         | -2.6965       |
| 0.5911        | 3.0   | 363  | 0.5908          | 0.0960         | -0.2480          | 0.7222             | 0.3440          | -241.9212      | -295.2642    | -2.6769         | -2.6941       |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
