---
base_model: mistralai/Mistral-7B-v0.3
datasets:
- llama-duo/synth_summarize_dataset_dedup
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: mistral_7b_0_3-summarize-gpt4o-128k
  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-summarize-gpt4o-128k

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_summarize_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0012

## 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: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6982        | 0.9980 | 245  | 1.8248          |
| 0.6596        | 2.0    | 491  | 1.8338          |
| 0.6197        | 2.9980 | 736  | 1.8432          |
| 0.6011        | 4.0    | 982  | 1.8707          |
| 0.5805        | 4.9980 | 1227 | 1.9009          |
| 0.5585        | 6.0    | 1473 | 1.9298          |
| 0.5413        | 6.9980 | 1718 | 1.9540          |
| 0.5295        | 8.0    | 1964 | 1.9814          |
| 0.5154        | 8.9980 | 2209 | 1.9979          |
| 0.508         | 9.9796 | 2450 | 2.0012          |


### Framework versions

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