---
base_model: mistralai/Mistral-7B-v0.3
datasets:
- llama-duo/synth_closed_qa_dataset_dedup
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: mistral_7b_0_3-closedqa-gpt4o-100k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mistral_7b_0_3-closedqa-gpt4o-100k

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the llama-duo/synth_closed_qa_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7580

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7127        | 1.0   | 146  | 1.7010          |
| 0.6581        | 2.0   | 292  | 1.6853          |
| 0.6323        | 3.0   | 438  | 1.6891          |
| 0.6067        | 4.0   | 584  | 1.7035          |
| 0.591         | 5.0   | 730  | 1.7226          |
| 0.5752        | 6.0   | 876  | 1.7259          |
| 0.5603        | 7.0   | 1022 | 1.7422          |
| 0.5632        | 8.0   | 1168 | 1.7483          |
| 0.5497        | 9.0   | 1314 | 1.7570          |
| 0.5353        | 10.0  | 1460 | 1.7580          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1