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---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- 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 [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5381
- Rewards/chosen: -0.0977
- Rewards/rejected: -0.7746
- Rewards/accuracies: 0.7183
- Rewards/margins: 0.6768
- Logps/rejected: -237.3503
- Logps/chosen: -283.6626
- Logits/rejected: -1.8216
- Logits/chosen: -1.9102
## 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: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5546 | 1.0 | 968 | 0.5678 | -0.0091 | -0.4982 | 0.7054 | 0.4891 | -234.5862 | -282.7758 | -1.8508 | -1.9394 |
| 0.5491 | 2.0 | 1936 | 0.5438 | -0.0836 | -0.7251 | 0.7192 | 0.6414 | -236.8553 | -283.5217 | -1.8279 | -1.9162 |
| 0.5463 | 3.0 | 2904 | 0.5381 | -0.0977 | -0.7746 | 0.7183 | 0.6768 | -237.3503 | -283.6626 | -1.8216 | -1.9102 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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