metadata
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: []
bbdeci7b-sft-lora-dpo-lora
This model is a SFT then DPO fine-tuned version of Deci/DeciLM-7B on the HuggingFaceH4/ultrachat_200k for SFT and the 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