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---
base_model: HuggingFaceH4/mistral-7b-sft-beta
library_name: peft
license: mit
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-lora
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-lora
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistral-7b-sft-beta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5082
- Rewards/chosen: 0.0025
- Rewards/rejected: -0.9047
- Rewards/accuracies: 0.7222
- Rewards/margins: 0.9072
- Logps/rejected: -276.6852
- Logps/chosen: -271.8461
- Logits/rejected: -2.7167
- Logits/chosen: -2.7365
## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5795 | 0.1047 | 100 | 0.5875 | 0.0265 | -0.3721 | 0.6825 | 0.3986 | -271.3593 | -271.6063 | -2.7688 | -2.7900 |
| 0.5449 | 0.2094 | 200 | 0.5520 | 0.0601 | -0.5726 | 0.7103 | 0.6327 | -273.3645 | -271.2704 | -2.7792 | -2.7981 |
| 0.545 | 0.3141 | 300 | 0.5320 | -0.0197 | -0.7637 | 0.7044 | 0.7439 | -275.2751 | -272.0686 | -2.7616 | -2.7803 |
| 0.4747 | 0.4187 | 400 | 0.5228 | -0.1728 | -0.9527 | 0.7004 | 0.7798 | -277.1651 | -273.5996 | -2.7532 | -2.7732 |
| 0.5367 | 0.5234 | 500 | 0.5175 | -0.2142 | -1.0435 | 0.7143 | 0.8293 | -278.0737 | -274.0135 | -2.7339 | -2.7540 |
| 0.5031 | 0.6281 | 600 | 0.5139 | -0.2939 | -1.1329 | 0.7024 | 0.8389 | -278.9670 | -274.8105 | -2.7071 | -2.7268 |
| 0.5057 | 0.7328 | 700 | 0.5084 | -0.0108 | -0.9049 | 0.7202 | 0.8941 | -276.6876 | -271.9794 | -2.7207 | -2.7404 |
| 0.5172 | 0.8375 | 800 | 0.5090 | -0.0300 | -0.9231 | 0.7183 | 0.8931 | -276.8697 | -272.1711 | -2.7173 | -2.7371 |
| 0.5173 | 0.9422 | 900 | 0.5084 | -0.0008 | -0.9080 | 0.7222 | 0.9072 | -276.7181 | -271.8789 | -2.7174 | -2.7372 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.14.6
- Tokenizers 0.20.1 |