File size: 3,345 Bytes
bf9d77d 05f301d bf9d77d 05f301d bf9d77d 05f301d bf9d77d 2de7880 bf9d77d 451e2d2 05f301d bf9d77d 05f301d bf9d77d 05f301d 451e2d2 |
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 |
---
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-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. -->
# zephyr-7b-dpo-full
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3183
- Rewards/chosen: -0.6032
- Rewards/rejected: -2.1160
- Rewards/accuracies: 0.8711
- Rewards/margins: 1.5128
- Logps/rejected: -584.2130
- Logps/chosen: -439.6992
- Logits/rejected: -5.8852
- Logits/chosen: -5.4031
## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5118 | 0.1151 | 100 | 0.5923 | -0.1120 | -0.4506 | 0.7070 | 0.3386 | -417.6701 | -390.5766 | -2.1984 | -2.2213 |
| 0.4206 | 0.2303 | 200 | 0.5055 | -0.2913 | -1.0785 | 0.8008 | 0.7872 | -480.4641 | -408.5089 | -3.2280 | -3.1644 |
| 0.4144 | 0.3454 | 300 | 0.4504 | -0.3084 | -1.2736 | 0.7773 | 0.9651 | -499.9700 | -410.2218 | -4.0963 | -3.8861 |
| 0.4011 | 0.4606 | 400 | 0.4135 | -0.4247 | -1.5332 | 0.8086 | 1.1086 | -525.9362 | -421.8441 | -4.8370 | -4.5018 |
| 0.3915 | 0.5757 | 500 | 0.3740 | -0.3892 | -1.7143 | 0.8516 | 1.3251 | -544.0394 | -418.2938 | -5.1877 | -4.7675 |
| 0.3726 | 0.6908 | 600 | 0.3468 | -0.4807 | -1.8892 | 0.8438 | 1.4085 | -561.5286 | -427.4439 | -5.6248 | -5.1461 |
| 0.3522 | 0.8060 | 700 | 0.3249 | -0.5431 | -2.0476 | 0.8789 | 1.5044 | -577.3692 | -433.6906 | -5.6819 | -5.2107 |
| 0.3643 | 0.9211 | 800 | 0.3183 | -0.6032 | -2.1160 | 0.8711 | 1.5128 | -584.2130 | -439.6992 | -5.8852 | -5.4031 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.19.1
|