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---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- trl
- orpo
- generated_from_trainer
model-index:
- name: mistral-orpo-mix-b0.05-l1024-pl512-lr5e-7-cosine
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-orpo-mix-b0.05-l1024-pl512-lr5e-7-cosine
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: 0.8648
- Rewards/chosen: -0.0405
- Rewards/rejected: -0.0502
- Rewards/accuracies: 0.6458
- Rewards/margins: 0.0097
- Logps/rejected: -1.0036
- Logps/chosen: -0.8096
- Logits/rejected: -2.9146
- Logits/chosen: -2.9040
- Nll Loss: 0.8392
- Log Odds Ratio: -0.6215
- Log Odds Chosen: 0.3802
## 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
- lr_scheduler_warmup_steps: 100
- 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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 0.9159 | 1.0 | 105 | 0.8794 | -0.0421 | -0.0499 | 0.6302 | 0.0078 | -0.9975 | -0.8413 | -2.8931 | -2.8875 | 0.8561 | -0.6429 | 0.3024 |
| 0.8397 | 2.0 | 211 | 0.8612 | -0.0404 | -0.0495 | 0.6458 | 0.0092 | -0.9902 | -0.8071 | -2.8882 | -2.8794 | 0.8366 | -0.6257 | 0.3555 |
| 0.7808 | 2.99 | 315 | 0.8648 | -0.0405 | -0.0502 | 0.6458 | 0.0097 | -1.0036 | -0.8096 | -2.9146 | -2.9040 | 0.8392 | -0.6215 | 0.3802 |
### Framework versions
- Transformers 4.39.0
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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