---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mistral-sum-r16a16longer
  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/sebastien-roig/mistral-sum/runs/1n5xzu6f)
# mistral-sum-r16a16longer

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: 1.6498

## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.196         | 0.0331 | 20   | 1.7916          |
| 1.6952        | 0.0663 | 40   | 1.7285          |
| 1.6458        | 0.0994 | 60   | 1.7016          |
| 1.6835        | 0.1326 | 80   | 1.6930          |
| 1.636         | 0.1657 | 100  | 1.6898          |
| 1.6294        | 0.1988 | 120  | 1.6890          |
| 1.67          | 0.2320 | 140  | 1.6813          |
| 1.6695        | 0.2651 | 160  | 1.6818          |
| 1.6442        | 0.2983 | 180  | 1.6784          |
| 1.6376        | 0.3314 | 200  | 1.6720          |
| 1.6094        | 0.3645 | 220  | 1.6692          |
| 1.6205        | 0.3977 | 240  | 1.6700          |
| 1.6372        | 0.4308 | 260  | 1.6663          |
| 1.6511        | 0.4640 | 280  | 1.6675          |
| 1.6071        | 0.4971 | 300  | 1.6705          |
| 1.6609        | 0.5302 | 320  | 1.6615          |
| 1.6039        | 0.5634 | 340  | 1.6576          |
| 1.6411        | 0.5965 | 360  | 1.6545          |
| 1.6363        | 0.6297 | 380  | 1.6551          |
| 1.6341        | 0.6628 | 400  | 1.6512          |
| 1.6123        | 0.6959 | 420  | 1.6492          |
| 1.6368        | 0.7291 | 440  | 1.6508          |
| 1.6265        | 0.7622 | 460  | 1.6513          |
| 1.6028        | 0.7954 | 480  | 1.6504          |
| 1.6229        | 0.8285 | 500  | 1.6498          |


### Framework versions

- PEFT 0.11.2.dev0
- Transformers 4.42.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1