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---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- alignment_handbook-handbook
- generated_from_trainer
datasets:
- princeton-nlp/mistral-instruct-ultrafeedback
model-index:
- name: Mistral-7B-Instruct-v0.2-MI-6e-7
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/tengxiao01/huggingface/runs/4cfe527t)
# Mistral-7B-Instruct-v0.2-MI-6e-7
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 princeton-nlp/mistral-instruct-ultrafeedback dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5201
- Rewards/chosen: -0.5693
- Rewards/rejected: -0.6258
- Rewards/accuracies: 0.5691
- Rewards/margins: 0.0565
- Logps/rejected: -0.6258
- Logps/chosen: -0.5693
- Logits/rejected: -3.4036
- Logits/chosen: -3.4095
## 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: 6e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 16
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.4828 | 0.8573 | 400 | 1.5201 | -0.5693 | -0.6258 | 0.5691 | 0.0565 | -0.6258 | -0.5693 | -3.4036 | -3.4095 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1
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