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

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6422

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4251        | 0.0   | 10   | 1.7924          |
| 1.3175        | 0.01  | 20   | 1.7542          |
| 1.7841        | 0.01  | 30   | 1.7322          |
| 2.0421        | 0.01  | 40   | 1.7294          |
| 2.669         | 0.02  | 50   | 1.7471          |
| 1.314         | 0.02  | 60   | 1.7153          |
| 1.4678        | 0.02  | 70   | 1.6989          |
| 1.7679        | 0.03  | 80   | 1.6928          |
| 2.0057        | 0.03  | 90   | 1.7002          |
| 2.5086        | 0.03  | 100  | 1.7053          |
| 1.3326        | 0.04  | 110  | 1.6931          |
| 1.3984        | 0.04  | 120  | 1.6823          |
| 1.8045        | 0.04  | 130  | 1.6807          |
| 1.8764        | 0.05  | 140  | 1.6812          |
| 2.5524        | 0.05  | 150  | 1.6825          |
| 1.2854        | 0.05  | 160  | 1.6766          |
| 1.3712        | 0.06  | 170  | 1.6709          |
| 1.8211        | 0.06  | 180  | 1.6660          |
| 2.0365        | 0.06  | 190  | 1.6778          |
| 2.4664        | 0.07  | 200  | 1.6938          |
| 1.3405        | 0.07  | 210  | 1.6712          |
| 1.3856        | 0.07  | 220  | 1.6666          |
| 1.5553        | 0.08  | 230  | 1.6586          |
| 1.8616        | 0.08  | 240  | 1.6613          |
| 2.4064        | 0.09  | 250  | 1.6666          |
| 1.3446        | 0.09  | 260  | 1.6681          |
| 1.386         | 0.09  | 270  | 1.6645          |
| 1.6508        | 0.1   | 280  | 1.6582          |
| 1.8588        | 0.1   | 290  | 1.6600          |
| 2.3148        | 0.1   | 300  | 1.6524          |
| 1.2785        | 0.11  | 310  | 1.6549          |
| 1.2727        | 0.11  | 320  | 1.6517          |
| 1.5971        | 0.11  | 330  | 1.6486          |
| 1.7811        | 0.12  | 340  | 1.6540          |
| 2.3368        | 0.12  | 350  | 1.6596          |
| 1.2513        | 0.12  | 360  | 1.6578          |
| 1.4403        | 0.13  | 370  | 1.6429          |
| 1.8051        | 0.13  | 380  | 1.6462          |
| 1.8214        | 0.13  | 390  | 1.6469          |
| 2.4691        | 0.14  | 400  | 1.6654          |
| 1.2895        | 0.14  | 410  | 1.6543          |
| 1.3192        | 0.14  | 420  | 1.6435          |
| 1.7031        | 0.15  | 430  | 1.6438          |
| 1.8647        | 0.15  | 440  | 1.6402          |
| 2.398         | 0.15  | 450  | 1.6444          |
| 1.3195        | 0.16  | 460  | 1.6445          |
| 1.4008        | 0.16  | 470  | 1.6407          |
| 1.6925        | 0.16  | 480  | 1.6380          |
| 1.8432        | 0.17  | 490  | 1.6396          |
| 2.5103        | 0.17  | 500  | 1.6422          |


### Framework versions

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