---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.1
model-index:
- name: mistral-7b-instruct-autextification2024
  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-7b-instruct-autextification2024

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8230

## 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: constant
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7076        | 0.0   | 10   | 2.0916          |
| 1.54          | 0.01  | 20   | 2.0382          |
| 2.0394        | 0.01  | 30   | 1.9987          |
| 2.3388        | 0.01  | 40   | 1.9706          |
| 3.0378        | 0.02  | 50   | 1.9866          |
| 1.511         | 0.02  | 60   | 1.9453          |
| 1.6499        | 0.02  | 70   | 1.9309          |
| 1.9693        | 0.03  | 80   | 1.9168          |
| 2.2389        | 0.03  | 90   | 1.9169          |
| 2.7812        | 0.03  | 100  | 1.9367          |
| 1.542         | 0.04  | 110  | 1.9202          |
| 1.574         | 0.04  | 120  | 1.9088          |
| 1.9916        | 0.04  | 130  | 1.8989          |
| 2.081         | 0.05  | 140  | 1.8862          |
| 2.768         | 0.05  | 150  | 1.9108          |
| 1.4699        | 0.05  | 160  | 1.8984          |
| 1.5366        | 0.06  | 170  | 1.8877          |
| 2.0133        | 0.06  | 180  | 1.8812          |
| 2.2186        | 0.06  | 190  | 1.8795          |
| 2.7003        | 0.07  | 200  | 1.8882          |
| 1.5169        | 0.07  | 210  | 1.8720          |
| 1.5444        | 0.07  | 220  | 1.8801          |
| 1.726         | 0.08  | 230  | 1.8732          |
| 2.0348        | 0.08  | 240  | 1.8657          |
| 2.6121        | 0.09  | 250  | 1.8702          |
| 1.5258        | 0.09  | 260  | 1.8655          |
| 1.5423        | 0.09  | 270  | 1.8733          |
| 1.8095        | 0.1   | 280  | 1.8505          |
| 2.0462        | 0.1   | 290  | 1.8455          |
| 2.5442        | 0.1   | 300  | 1.8552          |
| 1.4565        | 0.11  | 310  | 1.8586          |
| 1.4278        | 0.11  | 320  | 1.8491          |
| 1.7626        | 0.11  | 330  | 1.8358          |
| 1.9469        | 0.12  | 340  | 1.8427          |
| 2.5378        | 0.12  | 350  | 1.8580          |
| 1.4248        | 0.12  | 360  | 1.8499          |
| 1.586         | 0.13  | 370  | 1.8378          |
| 1.9637        | 0.13  | 380  | 1.8311          |
| 1.9733        | 0.13  | 390  | 1.8352          |
| 2.6789        | 0.14  | 400  | 1.8543          |
| 1.4521        | 0.14  | 410  | 1.8411          |
| 1.4683        | 0.14  | 420  | 1.8428          |
| 1.862         | 0.15  | 430  | 1.8331          |
| 2.0159        | 0.15  | 440  | 1.8304          |
| 2.5851        | 0.15  | 450  | 1.8385          |
| 1.4911        | 0.16  | 460  | 1.8309          |
| 1.5463        | 0.16  | 470  | 1.8262          |
| 1.8454        | 0.16  | 480  | 1.8137          |
| 2.0086        | 0.17  | 490  | 1.8143          |
| 2.6965        | 0.17  | 500  | 1.8230          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2