metadata
base_model: princeton-nlp/Llama-3-Base-8B-SFT
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: Llama-3-Base-8B
results: []
Llama-3-Base-8B
This model is a fine-tuned version of princeton-nlp/Llama-3-Base-8B-SFT on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6285
- Rewards/chosen: 0.5979
- Rewards/rejected: 0.1801
- Rewards/accuracies: 0.6620
- Rewards/margins: 0.4178
- Logps/rejected: -2212.5046
- Logps/chosen: -2612.9824
- Logits/rejected: -1.3033
- Logits/chosen: -1.3358
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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6694 | 0.03 | 100 | 0.6733 | 0.4668 | 0.3687 | 0.5500 | 0.0980 | -2193.6436 | -2626.0984 | -1.2047 | -1.2463 |
| 0.6496 | 0.05 | 200 | 0.6497 | 0.8935 | 0.6578 | 0.6040 | 0.2357 | -2164.7385 | -2583.4270 | -1.1621 | -1.2030 |
| 0.6358 | 0.08 | 300 | 0.6672 | 0.6703 | 0.4436 | 0.5900 | 0.2266 | -2186.1528 | -2605.7471 | -1.2202 | -1.2617 |
| 0.6783 | 0.1 | 400 | 0.7144 | 0.2834 | 0.0925 | 0.5680 | 0.1909 | -2221.2676 | -2644.4390 | -1.3598 | -1.4017 |
| 0.751 | 0.13 | 500 | 0.6889 | 1.3453 | 0.9758 | 0.6020 | 0.3696 | -2132.9402 | -2538.2405 | -1.4750 | -1.5419 |
| 0.6921 | 0.16 | 600 | 0.6644 | 0.8464 | 0.5451 | 0.6220 | 0.3014 | -2176.0090 | -2588.1318 | -1.2841 | -1.3381 |
| 0.6437 | 0.18 | 700 | 0.6724 | 0.8250 | 0.4796 | 0.6420 | 0.3454 | -2182.5566 | -2590.2764 | -1.4526 | -1.4817 |
| 0.8109 | 0.21 | 800 | 0.6655 | 1.1490 | 0.7473 | 0.6380 | 0.4017 | -2155.7832 | -2557.8708 | -1.5267 | -1.5761 |
| 0.6725 | 0.24 | 900 | 0.6836 | 1.4258 | 0.9989 | 0.6160 | 0.4269 | -2130.6240 | -2530.1914 | -1.4486 | -1.4910 |
| 0.7027 | 0.26 | 1000 | 0.6690 | 0.8152 | 0.4729 | 0.6260 | 0.3424 | -2183.2278 | -2591.2505 | -1.5095 | -1.5565 |
| 0.6421 | 0.29 | 1100 | 0.6513 | 0.5281 | 0.1941 | 0.6640 | 0.3340 | -2211.1040 | -2619.9661 | -1.5382 | -1.5785 |
| 0.6217 | 0.31 | 1200 | 0.6436 | 0.7372 | 0.3396 | 0.6460 | 0.3976 | -2196.5581 | -2599.0544 | -1.6345 | -1.6765 |
| 0.7365 | 0.34 | 1300 | 0.6400 | 0.9183 | 0.5227 | 0.6240 | 0.3956 | -2178.2437 | -2580.9446 | -1.5597 | -1.6009 |
| 0.7057 | 0.37 | 1400 | 0.6468 | 0.9514 | 0.5619 | 0.6140 | 0.3895 | -2174.3254 | -2577.6377 | -1.6716 | -1.7117 |
| 0.6396 | 0.39 | 1500 | 0.6498 | 0.9546 | 0.5405 | 0.6400 | 0.4141 | -2176.4675 | -2577.3193 | -1.6244 | -1.6600 |
| 0.5835 | 0.42 | 1600 | 0.6488 | 0.9504 | 0.5356 | 0.6480 | 0.4148 | -2176.9568 | -2577.7402 | -1.6255 | -1.6706 |
| 0.629 | 0.44 | 1700 | 0.6501 | 1.2484 | 0.8056 | 0.6100 | 0.4428 | -2149.9568 | -2547.9316 | -1.5737 | -1.6192 |
| 0.6495 | 0.47 | 1800 | 0.6440 | 1.2029 | 0.7629 | 0.6280 | 0.4400 | -2154.2307 | -2552.4846 | -1.4589 | -1.4973 |
| 0.6465 | 0.5 | 1900 | 0.6641 | 0.2111 | -0.0941 | 0.6280 | 0.3052 | -2239.9255 | -2651.6641 | -1.4961 | -1.5323 |
| 0.6866 | 0.52 | 2000 | 0.6480 | 0.5747 | 0.1977 | 0.6600 | 0.3770 | -2210.75 | -2615.3054 | -1.4509 | -1.4934 |
| 0.6441 | 0.55 | 2100 | 0.6358 | 0.8809 | 0.4502 | 0.6480 | 0.4307 | -2185.4985 | -2584.6841 | -1.4418 | -1.4842 |
| 0.6752 | 0.58 | 2200 | 0.6346 | 0.9311 | 0.5075 | 0.6560 | 0.4236 | -2179.7668 | -2579.6636 | -1.3193 | -1.3656 |
| 0.5646 | 0.6 | 2300 | 0.6396 | 0.6599 | 0.2912 | 0.6480 | 0.3686 | -2201.3948 | -2606.7883 | -1.2832 | -1.3116 |
| 0.6519 | 0.63 | 2400 | 0.6451 | 0.4237 | 0.0937 | 0.6400 | 0.3300 | -2221.1460 | -2630.4050 | -1.4460 | -1.4777 |
| 0.6292 | 0.65 | 2500 | 0.6313 | 0.8682 | 0.4231 | 0.6460 | 0.4452 | -2188.2095 | -2585.9512 | -1.4040 | -1.4397 |
| 0.5985 | 0.68 | 2600 | 0.6274 | 0.8396 | 0.3650 | 0.6640 | 0.4746 | -2194.0144 | -2588.8174 | -1.3580 | -1.3860 |
| 0.6323 | 0.71 | 2700 | 0.6328 | 0.6585 | 0.2012 | 0.6640 | 0.4573 | -2210.3958 | -2606.9260 | -1.2622 | -1.2938 |
| 0.6174 | 0.73 | 2800 | 0.6305 | 0.8505 | 0.3762 | 0.6580 | 0.4744 | -2192.8989 | -2587.7209 | -1.3312 | -1.3635 |
| 0.5972 | 0.76 | 2900 | 0.6310 | 0.6521 | 0.2290 | 0.6600 | 0.4231 | -2207.6130 | -2607.5659 | -1.3492 | -1.3840 |
| 0.6645 | 0.79 | 3000 | 0.6291 | 0.7035 | 0.2579 | 0.6520 | 0.4456 | -2204.7251 | -2602.4238 | -1.3330 | -1.3678 |
| 0.5786 | 0.81 | 3100 | 0.6310 | 0.5452 | 0.1222 | 0.6580 | 0.4230 | -2218.2944 | -2618.2534 | -1.3173 | -1.3498 |
| 0.604 | 0.84 | 3200 | 0.6375 | 0.3327 | -0.0527 | 0.6540 | 0.3854 | -2235.7852 | -2639.5032 | -1.3444 | -1.3760 |
| 0.6704 | 0.86 | 3300 | 0.6269 | 0.7327 | 0.2896 | 0.6540 | 0.4431 | -2201.5579 | -2599.5049 | -1.3241 | -1.3585 |
| 0.6365 | 0.89 | 3400 | 0.6271 | 0.6900 | 0.2577 | 0.6560 | 0.4323 | -2204.7437 | -2603.7739 | -1.3038 | -1.3371 |
| 0.6621 | 0.92 | 3500 | 0.6279 | 0.6303 | 0.2073 | 0.6580 | 0.4230 | -2209.7827 | -2609.7432 | -1.2991 | -1.3321 |
| 0.6597 | 0.94 | 3600 | 0.6294 | 0.5540 | 0.1441 | 0.6580 | 0.4099 | -2216.1082 | -2617.3774 | -1.3028 | -1.3348 |
| 0.671 | 0.97 | 3700 | 0.6285 | 0.5945 | 0.1774 | 0.6600 | 0.4171 | -2212.7783 | -2613.3303 | -1.3033 | -1.3358 |
| 0.6328 | 0.99 | 3800 | 0.6283 | 0.5985 | 0.1803 | 0.6580 | 0.4182 | -2212.4902 | -2612.9258 | -1.3032 | -1.3356 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2