File size: 5,292 Bytes
af3f8c8 63a2487 af3f8c8 63a2487 af3f8c8 63a2487 af3f8c8 63a2487 af3f8c8 |
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 |
---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: alignment-handbook/zephyr-7b-sft-full
datasets:
- generation/GPT4
model-index:
- name: zephyr-dpop-qlora-gpt4-5e-6-epoch3
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. -->
# zephyr-dpop-qlora-gpt4-5e-6-epoch3
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the generation/GPT4 dataset.
It achieves the following results on the evaluation set:
- Loss: 14.3852
- Positive Losses: 141.6597
- Dpo Losses: 0.6849
- Rewards/chosen: -1.4061
- Rewards/rejected: -2.0012
- Rewards/accuracies: 0.6667
- Rewards/margins: 0.5951
- Rewards/margins Max: 2.2885
- Rewards/margins Min: -1.0995
- Rewards/margins Std: 1.4978
- Logps/rejected: -459.3069
- Logps/chosen: -425.8328
- Logits/rejected: -2.2783
- Logits/chosen: -2.3207
## 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-06
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Positive Losses | Dpo Losses | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Rewards/margins Max | Rewards/margins Min | Rewards/margins Std | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:----------:|:--------------:|:----------------:|:------------------:|:---------------:|:-------------------:|:-------------------:|:-------------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5432 | 0.28 | 100 | 1.5490 | 8.3683 | 0.6723 | -0.0507 | -0.1015 | 0.5992 | 0.0508 | 0.2567 | -0.1414 | 0.1757 | -269.3354 | -290.2917 | -2.6677 | -2.7099 |
| 0.4843 | 0.56 | 200 | 3.6354 | 28.9322 | 0.6415 | -0.2537 | -0.4297 | 0.6349 | 0.1759 | 0.7364 | -0.3533 | 0.4858 | -302.1486 | -310.5943 | -2.5589 | -2.6000 |
| 0.2828 | 0.85 | 300 | 6.8046 | 61.7689 | 0.6346 | -0.6003 | -0.8503 | 0.6508 | 0.2500 | 1.0085 | -0.4868 | 0.6679 | -344.2117 | -345.2526 | -2.5349 | -2.5759 |
| 0.3355 | 1.13 | 400 | 11.4158 | 108.7399 | 0.6572 | -1.0761 | -1.4209 | 0.6548 | 0.3447 | 1.4626 | -0.7661 | 0.9968 | -401.2702 | -392.8341 | -2.3773 | -2.4155 |
| 0.3438 | 1.41 | 500 | 10.6413 | 101.3525 | 0.6381 | -1.0007 | -1.3406 | 0.6865 | 0.3399 | 1.3353 | -0.6338 | 0.8805 | -393.2457 | -385.2938 | -2.4471 | -2.4907 |
| 0.2144 | 1.69 | 600 | 8.5896 | 79.7998 | 0.6267 | -0.7817 | -1.2135 | 0.6865 | 0.4318 | 1.5951 | -0.6661 | 1.0047 | -380.5318 | -363.3914 | -2.3029 | -2.3438 |
| 0.3314 | 1.97 | 700 | 11.1651 | 107.2969 | 0.6525 | -1.0595 | -1.5150 | 0.6627 | 0.4555 | 1.7776 | -0.8450 | 1.1660 | -410.6869 | -391.1705 | -2.3025 | -2.3432 |
| 0.1352 | 2.25 | 800 | 13.3571 | 130.9070 | 0.6700 | -1.2986 | -1.8184 | 0.6627 | 0.5198 | 2.0225 | -0.9603 | 1.3296 | -441.0237 | -415.0786 | -2.2901 | -2.3320 |
| 0.2348 | 2.54 | 900 | 14.7241 | 145.9081 | 0.6904 | -1.4488 | -2.0053 | 0.6706 | 0.5564 | 2.1801 | -1.0958 | 1.4586 | -459.7108 | -430.1044 | -2.2661 | -2.3085 |
| 0.1369 | 2.82 | 1000 | 14.5955 | 143.9389 | 0.6869 | -1.4291 | -2.0251 | 0.6627 | 0.5959 | 2.2953 | -1.1073 | 1.5052 | -461.6887 | -428.1342 | -2.2738 | -2.3165 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2 |