File size: 17,835 Bytes
91aef91 c3d5b59 c78836d 91aef91 1a33399 97f50f9 e0adbef 97f50f9 1a33399 91aef91 1a33399 91aef91 1a33399 e0adbef 1a33399 e0adbef 1a33399 e0adbef 1a33399 e0adbef 1a33399 e0adbef 91aef91 c78836d 91aef91 c78836d 91aef91 e0adbef 91aef91 e0adbef 91aef91 c78836d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 |
---
license: apache-2.0
base_model: nnheui/pythia-1.4b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: pythia-1.4b-dpo-full
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. -->
# pythia-1.4b-dpo-full
This model is a fine-tuned version of [nnheui/pythia-1.4b-sft-full](https://huggingface.co/nnheui/pythia-1.4b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5991
- Rewards/chosen: -1.875
- Rewards/rejected: -2.6406
- Rewards/accuracies: 0.7164
- Rewards/margins: 0.7734
- Logps/rejected: -604.0
- Logps/chosen: -580.0
- Logits/rejected: -1.4297
- Logits/chosen: -1.4062
- Logps/chosen Top Tokens: -0.0009
- Logps/rejected Top Tokens: -0.0009
- Logps/chosen Bottom Tokens: -13.9375
- Logps/rejected Bottom Tokens: -13.8125
## 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: 5e-07
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 4
- total_train_batch_size: 120
- total_eval_batch_size: 30
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/chosen Bottom Tokens | Logps/chosen Top Tokens | Logps/rejected | Logps/rejected Bottom Tokens | Logps/rejected Top Tokens | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:------:|:----:|:-------------:|:---------------:|:------------:|:--------------------------:|:-----------------------:|:--------------:|:----------------------------:|:-------------------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.678 | 0.1963 | 100 | -1.0938 | -1.1562 | -396.0 | -14.0625 | -0.0009 | -344.0 | -14.0 | -0.0009 | 0.6789 | 0.5881 | -0.0275 | 0.0332 | -0.0608 |
| 0.645 | 0.3925 | 200 | -1.1562 | -1.2031 | -422.0 | -14.375 | -0.0009 | -380.0 | -14.3125 | -0.0009 | 0.6489 | 0.6448 | -0.2871 | 0.1367 | -0.4238 |
| 0.6396 | 0.5888 | 300 | -1.1875 | -1.2344 | -438.0 | -14.375 | -0.0007 | -406.0 | -14.3125 | -0.0008 | 0.6304 | 0.6627 | -0.4512 | 0.2275 | -0.6797 |
| 0.6102 | 0.7851 | 400 | -1.1875 | -1.2344 | -444.0 | -14.3125 | -0.0007 | -414.0 | -14.25 | -0.0007 | 0.6268 | 0.6567 | -0.5039 | 0.2578 | -0.7617 |
| 0.6084 | 0.9814 | 500 | -1.1953 | -1.2422 | -446.0 | -14.375 | -0.0007 | -416.0 | -14.3125 | -0.0007 | 0.6259 | 0.6567 | -0.5234 | 0.2617 | -0.7852 |
| 0.6115 | 1.1776 | 600 | 0.6121 | -0.5547 | -0.8789 | 0.6806 | 0.3242 | -426.0 | -450.0 | -1.2578 | -1.2109 | -0.0006 | -0.0006 | -14.25 | -14.125 |
| 0.607 | 1.3739 | 700 | 0.6068 | -0.6641 | -1.0078 | 0.6985 | 0.3418 | -438.0 | -460.0 | -1.2812 | -1.2344 | -0.0006 | -0.0006 | -14.1875 | -14.125 |
| 0.5764 | 1.5702 | 800 | 0.5996 | -0.75 | -1.1406 | 0.6866 | 0.3887 | -452.0 | -468.0 | -1.3125 | -1.2656 | -0.0007 | -0.0007 | -14.25 | -14.125 |
| 0.5903 | 1.7664 | 900 | 0.5984 | -0.5898 | -0.9648 | 0.7045 | 0.3770 | -434.0 | -452.0 | -1.3125 | -1.2656 | -0.0006 | -0.0006 | -14.25 | -14.125 |
| 0.5697 | 1.9627 | 1000 | 0.5922 | -0.7383 | -1.1562 | 0.6866 | 0.4160 | -454.0 | -468.0 | -1.3125 | -1.2734 | -0.0007 | -0.0006 | -14.0625 | -14.0 |
| 0.5573 | 2.1590 | 1100 | 0.5854 | -0.8203 | -1.2812 | 0.6985 | 0.4570 | -466.0 | -476.0 | -1.3281 | -1.2891 | -0.0006 | -0.0006 | -14.125 | -14.0 |
| 0.5439 | 2.3553 | 1200 | 0.5845 | -1.1016 | -1.6172 | 0.6866 | 0.5078 | -498.0 | -504.0 | -1.3672 | -1.3281 | -0.0007 | -0.0006 | -14.0625 | -13.9375 |
| 0.5487 | 2.5515 | 1300 | 0.5801 | -0.8906 | -1.3828 | 0.6925 | 0.4980 | -476.0 | -482.0 | -1.3828 | -1.3438 | -0.0007 | -0.0006 | -14.0625 | -14.0 |
| 0.543 | 2.7478 | 1400 | 0.5785 | -0.8672 | -1.3516 | 0.7134 | 0.4863 | -474.0 | -480.0 | -1.375 | -1.3359 | -0.0007 | -0.0006 | -14.0625 | -13.9375 |
| 0.5382 | 2.9441 | 1500 | 0.5711 | -1.1172 | -1.6641 | 0.6955 | 0.5508 | -504.0 | -506.0 | -1.3906 | -1.3516 | -0.0007 | -0.0006 | -14.125 | -14.0 |
| 0.5117 | 3.1403 | 1600 | 0.5712 | -1.25 | -1.8281 | 0.7045 | 0.5742 | -520.0 | -520.0 | -1.3984 | -1.3594 | -0.0007 | -0.0006 | -14.125 | -14.0 |
| 0.4983 | 3.3366 | 1700 | 0.5703 | -1.1641 | -1.75 | 0.7015 | 0.5859 | -512.0 | -510.0 | -1.4062 | -1.3672 | -0.0007 | -0.0007 | -14.125 | -14.0 |
| 0.4976 | 3.5329 | 1800 | 0.5709 | -1.2656 | -1.8828 | 0.7254 | 0.6133 | -524.0 | -520.0 | -1.4141 | -1.375 | -0.0007 | -0.0007 | -14.125 | -14.0625 |
| 0.4956 | 3.7291 | 1900 | 0.5754 | -1.2266 | -1.8047 | 0.7164 | 0.5781 | -516.0 | -516.0 | -1.4062 | -1.3672 | -0.0008 | -0.0008 | -14.0625 | -13.9375 |
| 0.4996 | 3.9254 | 2000 | 0.5722 | -1.2578 | -1.8516 | 0.7045 | 0.6016 | -524.0 | -520.0 | -1.4062 | -1.375 | -0.0008 | -0.0008 | -14.0625 | -13.9375 |
| 0.4588 | 4.1217 | 2100 | 0.5748 | -1.4141 | -2.0312 | 0.7343 | 0.6211 | -540.0 | -536.0 | -1.4062 | -1.375 | -0.0009 | -0.0009 | -14.0 | -13.875 |
| 0.4555 | 4.3180 | 2200 | 0.5743 | -1.2969 | -1.9141 | 0.7164 | 0.6172 | -528.0 | -524.0 | -1.4219 | -1.3906 | -0.0009 | -0.0009 | -13.9375 | -13.8125 |
| 0.4625 | 4.5142 | 2300 | 0.5735 | -1.3047 | -1.9297 | 0.7134 | 0.625 | -532.0 | -524.0 | -1.4141 | -1.3828 | -0.0008 | -0.0008 | -14.0 | -13.875 |
| 0.469 | 4.7105 | 2400 | 0.5743 | -1.4766 | -2.1406 | 0.7194 | 0.6562 | -552.0 | -540.0 | -1.4375 | -1.3984 | -0.0009 | -0.0009 | -14.0 | -13.875 |
| 0.4796 | 4.9068 | 2500 | 0.5750 | -1.3281 | -1.9766 | 0.7134 | 0.6484 | -536.0 | -528.0 | -1.4375 | -1.3984 | -0.0009 | -0.0009 | -14.0 | -13.875 |
| 0.4082 | 5.1030 | 2600 | 0.5818 | -1.6016 | -2.2656 | 0.7194 | 0.6602 | -564.0 | -552.0 | -1.4453 | -1.4062 | -0.0009 | -0.0009 | -14.0 | -13.875 |
| 0.4193 | 5.2993 | 2700 | 0.5803 | -1.4922 | -2.1406 | 0.7194 | 0.6523 | -552.0 | -544.0 | -1.4375 | -1.3984 | -0.0009 | -0.0009 | -14.0 | -13.8125 |
| 0.419 | 5.4956 | 2800 | 0.5795 | -1.625 | -2.3281 | 0.7194 | 0.7031 | -572.0 | -556.0 | -1.4375 | -1.3984 | -0.0009 | -0.0009 | -14.0 | -13.875 |
| 0.4267 | 5.6919 | 2900 | 0.5780 | -1.6875 | -2.375 | 0.7134 | 0.6836 | -576.0 | -564.0 | -1.4375 | -1.4062 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
| 0.402 | 5.8881 | 3000 | 0.5828 | -1.6484 | -2.3594 | 0.7254 | 0.7109 | -572.0 | -560.0 | -1.4453 | -1.4062 | -0.0009 | -0.0009 | -13.9375 | -13.8125 |
| 0.3656 | 6.0844 | 3100 | 0.5844 | -1.6875 | -2.4062 | 0.7015 | 0.7227 | -580.0 | -564.0 | -1.4375 | -1.4062 | -0.0009 | -0.0009 | -14.0 | -13.875 |
| 0.3971 | 6.2807 | 3200 | 0.5873 | -1.6094 | -2.3281 | 0.7075 | 0.7148 | -572.0 | -556.0 | -1.4453 | -1.4141 | -0.0009 | -0.0009 | -14.0 | -13.8125 |
| 0.3923 | 6.4769 | 3300 | 0.5906 | -1.6875 | -2.4062 | 0.7075 | 0.7188 | -580.0 | -564.0 | -1.4453 | -1.4141 | -0.0009 | -0.0009 | -14.0 | -13.875 |
| 0.4011 | 6.6732 | 3400 | 0.5848 | -1.7109 | -2.4375 | 0.7254 | 0.7344 | -584.0 | -564.0 | -1.4375 | -1.4062 | -0.0009 | -0.0008 | -14.0 | -13.875 |
| 0.3838 | 6.8695 | 3500 | 0.5897 | -1.75 | -2.4844 | 0.7164 | 0.7305 | -584.0 | -568.0 | -1.4297 | -1.3984 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
| 0.3762 | 7.0658 | 3600 | 0.5910 | -1.7812 | -2.5312 | 0.7134 | 0.7422 | -592.0 | -572.0 | -1.4375 | -1.4062 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
| 0.3591 | 7.2620 | 3700 | 0.5895 | -1.7812 | -2.5312 | 0.7075 | 0.7578 | -592.0 | -572.0 | -1.4375 | -1.4062 | -0.0009 | -0.0009 | -14.0 | -13.875 |
| 0.3713 | 7.4583 | 3800 | 0.5956 | -1.7734 | -2.5312 | 0.7164 | 0.75 | -592.0 | -572.0 | -1.4297 | -1.3984 | -0.0009 | -0.0009 | -13.9375 | -13.8125 |
| 0.381 | 7.6546 | 3900 | 0.5948 | -1.8672 | -2.625 | 0.7164 | 0.7695 | -600.0 | -580.0 | -1.4375 | -1.4062 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
| 0.3639 | 7.8508 | 4000 | 0.5950 | -1.8672 | -2.625 | 0.7194 | 0.7578 | -600.0 | -580.0 | -1.4375 | -1.4062 | -0.0009 | -0.0009 | -13.9375 | -13.8125 |
| 0.3563 | 8.0471 | 4100 | 0.5939 | -1.8281 | -2.5781 | 0.7075 | 0.7539 | -596.0 | -576.0 | -1.4297 | -1.3984 | -0.0009 | -0.0009 | -13.9375 | -13.8125 |
| 0.3484 | 8.2434 | 4200 | 0.5969 | -1.875 | -2.6406 | 0.7045 | 0.7656 | -600.0 | -580.0 | -1.4375 | -1.4062 | -0.0009 | -0.0008 | -14.0 | -13.875 |
| 0.3359 | 8.4396 | 4300 | 0.5966 | -1.8828 | -2.6562 | 0.7045 | 0.7734 | -604.0 | -580.0 | -1.4375 | -1.4062 | -0.0009 | -0.0009 | -13.9375 | -13.8125 |
| 0.3639 | 8.6359 | 4400 | 0.5979 | -1.8516 | -2.5938 | 0.7075 | 0.7461 | -596.0 | -580.0 | -1.4297 | -1.3984 | -0.0009 | -0.0009 | -13.9375 | -13.8125 |
| 0.3563 | 8.8322 | 4500 | 0.5979 | -1.8594 | -2.625 | 0.7075 | 0.7617 | -600.0 | -580.0 | -1.4297 | -1.3984 | -0.0009 | -0.0009 | -13.9375 | -13.8125 |
| 0.353 | 9.0285 | 4600 | 0.5981 | -1.8672 | -2.625 | 0.6985 | 0.7617 | -600.0 | -580.0 | -1.4297 | -1.3984 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
| 0.3514 | 9.2247 | 4700 | 0.5979 | -1.8594 | -2.625 | 0.6985 | 0.7656 | -600.0 | -580.0 | -1.4297 | -1.3984 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
| 0.3434 | 9.4210 | 4800 | 0.5973 | -1.8672 | -2.6406 | 0.7015 | 0.7656 | -600.0 | -580.0 | -1.4297 | -1.4062 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
| 0.3492 | 9.6173 | 4900 | 0.5981 | -1.875 | -2.6406 | 0.7045 | 0.7578 | -600.0 | -580.0 | -1.4297 | -1.3984 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
| 0.3487 | 9.8135 | 5000 | 0.5967 | -1.8672 | -2.6406 | 0.7134 | 0.7734 | -600.0 | -580.0 | -1.4375 | -1.4062 | -0.0009 | -0.0008 | -13.9375 | -13.8125 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|