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---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- Dahoas/full-hh-rlhf
model-index:
- name: Mistral-7B-Instruct-v0.2-DPO
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. -->
# Mistral-7B-Instruct-v0.2-DPO
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the Dahoas/full-hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5782
- Rewards/chosen: -0.2120
- Rewards/rejected: -0.7002
- Rewards/accuracies: 0.6926
- Rewards/margins: 0.4883
- Logps/rejected: -296.2612
- Logps/chosen: -255.5737
- Logits/rejected: -2.4985
- Logits/chosen: -2.5472
## 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: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6628 | 0.06 | 100 | 0.6611 | 0.1337 | 0.0489 | 0.6317 | 0.0848 | -221.3471 | -221.0088 | -2.6721 | -2.7152 |
| 0.6203 | 0.11 | 200 | 0.6121 | -0.0960 | -0.4057 | 0.6609 | 0.3097 | -266.8084 | -243.9758 | -2.6213 | -2.6775 |
| 0.6134 | 0.17 | 300 | 0.6074 | -0.0623 | -0.3733 | 0.6702 | 0.3111 | -263.5724 | -240.6045 | -2.7988 | -2.8551 |
| 0.5967 | 0.23 | 400 | 0.5992 | -0.1315 | -0.5181 | 0.6782 | 0.3866 | -278.0497 | -247.5236 | -2.4576 | -2.5191 |
| 0.6216 | 0.29 | 500 | 0.5941 | -0.0370 | -0.4146 | 0.6721 | 0.3775 | -267.6940 | -238.0781 | -2.6879 | -2.7311 |
| 0.5919 | 0.34 | 600 | 0.5904 | -0.1509 | -0.5767 | 0.6865 | 0.4258 | -283.9072 | -249.4699 | -2.4044 | -2.4745 |
| 0.5769 | 0.4 | 700 | 0.5902 | -0.2407 | -0.6647 | 0.6772 | 0.4240 | -292.7129 | -258.4496 | -2.2190 | -2.2924 |
| 0.5725 | 0.46 | 800 | 0.5882 | -0.0462 | -0.4830 | 0.6837 | 0.4368 | -274.5383 | -238.9940 | -2.5276 | -2.5732 |
| 0.5814 | 0.51 | 900 | 0.5864 | -0.1178 | -0.5375 | 0.6811 | 0.4197 | -279.9914 | -246.1586 | -2.3355 | -2.4098 |
| 0.5514 | 0.57 | 1000 | 0.5839 | -0.1827 | -0.6505 | 0.6872 | 0.4678 | -291.2902 | -252.6515 | -2.4115 | -2.4855 |
| 0.5946 | 0.63 | 1100 | 0.5846 | -0.0669 | -0.5120 | 0.6846 | 0.4451 | -277.4430 | -241.0672 | -2.4475 | -2.5090 |
| 0.5988 | 0.69 | 1200 | 0.5829 | -0.2676 | -0.7315 | 0.6891 | 0.4638 | -299.3864 | -261.1408 | -2.4703 | -2.5293 |
| 0.5725 | 0.74 | 1300 | 0.5809 | -0.1107 | -0.5656 | 0.6878 | 0.4549 | -282.7961 | -245.4460 | -2.4590 | -2.5131 |
| 0.5719 | 0.8 | 1400 | 0.5793 | -0.2111 | -0.6982 | 0.6894 | 0.4871 | -296.0592 | -255.4868 | -2.4585 | -2.5096 |
| 0.5702 | 0.86 | 1500 | 0.5789 | -0.2663 | -0.7548 | 0.6888 | 0.4884 | -301.7152 | -261.0100 | -2.4746 | -2.5243 |
| 0.5854 | 0.91 | 1600 | 0.5783 | -0.2282 | -0.7193 | 0.6913 | 0.4911 | -298.1695 | -257.1977 | -2.5037 | -2.5523 |
| 0.578 | 0.97 | 1700 | 0.5782 | -0.2135 | -0.7018 | 0.6920 | 0.4884 | -296.4236 | -255.7232 | -2.4987 | -2.5475 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
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