File size: 2,875 Bytes
1b22adc d9c1301 1b22adc d9c1301 1b22adc d9c1301 1b22adc d9c1301 1b22adc d9c1301 1b22adc |
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 |
---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
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 is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4983
- Rewards/chosen: -2.4880
- Rewards/rejected: -3.6063
- Rewards/accuracies: 0.7695
- Rewards/margins: 1.1182
- Logps/rejected: -623.3074
- Logps/chosen: -511.4043
- Logits/rejected: 0.0233
- Logits/chosen: -0.4369
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5875 | 0.21 | 100 | 0.5814 | -0.6485 | -1.1103 | 0.6953 | 0.4618 | -373.7126 | -327.4548 | -1.8929 | -1.8392 |
| 0.5306 | 0.42 | 200 | 0.5258 | -1.1476 | -1.9595 | 0.7578 | 0.8118 | -458.6297 | -377.3649 | -0.1647 | -0.4835 |
| 0.5097 | 0.63 | 300 | 0.5079 | -2.3601 | -3.3817 | 0.7656 | 1.0216 | -600.8517 | -498.6086 | -0.0574 | -0.4658 |
| 0.4906 | 0.84 | 400 | 0.5000 | -2.3681 | -3.4811 | 0.7695 | 1.1129 | -610.7911 | -499.4172 | -0.0390 | -0.5081 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
|