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---
license: mit
base_model: HuggingFaceH4/mistral-7b-sft-beta
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-debug-regression
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-debug-regression
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: 0.7240
- Rewards/chosen: -4.3843
- Rewards/rejected: -7.9101
- Rewards/accuracies: 0.7640
- Rewards/margins: 3.5258
- Logps/rejected: -311.4621
- Logps/chosen: -319.5667
- Logits/rejected: -2.4790
- Logits/chosen: -2.5088
## 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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.533 | 0.26 | 500 | 0.5084 | -0.1902 | -1.3680 | 0.7780 | 1.1778 | -246.0413 | -277.6251 | -2.9319 | -2.9487 |
| 0.4907 | 0.52 | 1000 | 0.5234 | -0.3346 | -1.8153 | 0.7620 | 1.4807 | -250.5139 | -279.0693 | -2.8401 | -2.8442 |
| 0.4388 | 0.77 | 1500 | 0.5202 | -0.7856 | -2.2720 | 0.7920 | 1.4864 | -255.0812 | -283.5798 | -2.7420 | -2.7444 |
| 0.0651 | 1.03 | 2000 | 0.5049 | -1.0044 | -2.8702 | 0.7860 | 1.8658 | -261.0635 | -285.7675 | -2.7335 | -2.7412 |
| 0.0887 | 1.29 | 2500 | 0.5946 | -1.9888 | -3.9256 | 0.7480 | 1.9368 | -271.6175 | -295.6113 | -2.5940 | -2.6173 |
| 0.0747 | 1.55 | 3000 | 0.5748 | -1.9590 | -4.0271 | 0.7560 | 2.0681 | -272.6327 | -295.3135 | -2.4969 | -2.5205 |
| 0.101 | 1.81 | 3500 | 0.5783 | -1.9521 | -4.1853 | 0.7680 | 2.2332 | -274.2144 | -295.2442 | -2.5069 | -2.5278 |
| 0.0195 | 2.07 | 4000 | 0.6253 | -2.9322 | -5.7633 | 0.7600 | 2.8310 | -289.9938 | -305.0455 | -2.4935 | -2.5158 |
| 0.0191 | 2.32 | 4500 | 0.7215 | -4.2183 | -7.6216 | 0.7620 | 3.4034 | -308.5774 | -317.9060 | -2.4756 | -2.5036 |
| 0.0105 | 2.58 | 5000 | 0.7341 | -4.2607 | -7.7440 | 0.7600 | 3.4833 | -309.8016 | -318.3306 | -2.5156 | -2.5437 |
| 0.0092 | 2.84 | 5500 | 0.7330 | -4.3756 | -7.9435 | 0.7600 | 3.5679 | -311.7966 | -319.4794 | -2.4856 | -2.5149 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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