metadata
library_name: transformers
license: llama3.1
base_model: Magpie-Align/Llama-3.1-8B-Magpie-SFT-GMix-550K
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- Magpie-Align/MagpieLM-4B-DPO-Data-v0.1
model-index:
- name: Llama-3.1-8B-Magpie-SFT-GMix-550K-DPO-02Mix
results: []
Llama-3.1-8B-Magpie-SFT-GMix-550K-DPO-02Mix
This model is a fine-tuned version of Magpie-Align/Llama-3.1-8B-Magpie-SFT-GMix-550K on the Magpie-Align/MagpieLM-4B-DPO-Data-v0.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3866
- Rewards/chosen: -5.1623
- Rewards/rejected: -6.8930
- Rewards/accuracies: 0.8060
- Rewards/margins: 1.7307
- Logps/rejected: -1154.4679
- Logps/chosen: -990.1328
- Logits/rejected: -0.6102
- Logits/chosen: -0.6705
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: 2e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.686 | 0.0653 | 100 | 0.6856 | -0.0491 | -0.0616 | 0.6480 | 0.0125 | -471.3315 | -478.8181 | -0.7034 | -0.7427 |
| 0.6218 | 0.1306 | 200 | 0.6277 | -0.6128 | -0.7720 | 0.6960 | 0.1591 | -542.3653 | -535.1920 | -0.7771 | -0.8125 |
| 0.5705 | 0.1959 | 300 | 0.5545 | -2.4738 | -3.0052 | 0.7270 | 0.5314 | -765.6894 | -721.2881 | -0.7894 | -0.8230 |
| 0.4606 | 0.2612 | 400 | 0.5081 | -2.6780 | -3.3782 | 0.7560 | 0.7002 | -802.9893 | -741.7116 | -0.6813 | -0.7247 |
| 0.4314 | 0.3266 | 500 | 0.4787 | -3.6697 | -4.6026 | 0.7630 | 0.9329 | -925.4283 | -840.8740 | -0.6189 | -0.6691 |
| 0.449 | 0.3919 | 600 | 0.4533 | -3.7414 | -4.8019 | 0.7820 | 1.0604 | -945.3563 | -848.0514 | -0.6157 | -0.6681 |
| 0.4538 | 0.4572 | 700 | 0.4350 | -4.3858 | -5.6549 | 0.7890 | 1.2690 | -1030.6561 | -912.4920 | -0.5789 | -0.6331 |
| 0.35 | 0.5225 | 800 | 0.4186 | -4.7129 | -6.1662 | 0.8010 | 1.4533 | -1081.7843 | -945.1964 | -0.5778 | -0.6347 |
| 0.4153 | 0.5878 | 900 | 0.4108 | -4.9836 | -6.5320 | 0.7970 | 1.5484 | -1118.3677 | -972.2631 | -0.5895 | -0.6474 |
| 0.3935 | 0.6531 | 1000 | 0.3999 | -4.4303 | -5.9370 | 0.8110 | 1.5067 | -1058.8646 | -916.9379 | -0.6016 | -0.6598 |
| 0.3205 | 0.7184 | 1100 | 0.3950 | -5.1884 | -6.8827 | 0.8010 | 1.6943 | -1153.4371 | -992.7452 | -0.5846 | -0.6452 |
| 0.3612 | 0.7837 | 1200 | 0.3901 | -5.0426 | -6.7179 | 0.8040 | 1.6753 | -1136.9619 | -978.1701 | -0.6046 | -0.6637 |
| 0.3058 | 0.8490 | 1300 | 0.3877 | -5.1224 | -6.8428 | 0.8040 | 1.7204 | -1149.4465 | -986.1475 | -0.6087 | -0.6690 |
| 0.3467 | 0.9144 | 1400 | 0.3871 | -5.2335 | -6.9809 | 0.8090 | 1.7474 | -1163.2629 | -997.2610 | -0.6071 | -0.6672 |
| 0.3197 | 0.9797 | 1500 | 0.3867 | -5.1502 | -6.8793 | 0.8080 | 1.7291 | -1153.0979 | -988.9237 | -0.6120 | -0.6722 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1