---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
model-index:
- name: fine-tuning-dolphin-mistral-with-webglm-qa-with-lora_1
  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. -->

# fine-tuning-dolphin-mistral-with-webglm-qa-with-lora_1

This model is a fine-tuned version of [cognitivecomputations/dolphin-2.8-mistral-7b-v02](https://huggingface.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2999

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 60
- training_steps: 700
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7558        | 0.16  | 10   | 1.4842          |
| 1.4966        | 0.32  | 20   | 1.3367          |
| 1.2328        | 0.48  | 30   | 1.1282          |
| 0.9873        | 0.64  | 40   | 1.0817          |
| 0.9661        | 0.8   | 50   | 0.9967          |
| 0.8808        | 0.96  | 60   | 0.8844          |
| 0.7455        | 1.13  | 70   | 0.7337          |
| 0.6018        | 1.29  | 80   | 0.6164          |
| 0.4899        | 1.45  | 90   | 0.5440          |
| 0.4402        | 1.61  | 100  | 0.4971          |
| 0.4154        | 1.77  | 110  | 0.4555          |
| 0.4025        | 1.93  | 120  | 0.4238          |
| 0.3992        | 2.09  | 130  | 0.4007          |
| 0.3585        | 2.25  | 140  | 0.3862          |
| 0.3369        | 2.41  | 150  | 0.3666          |
| 0.3328        | 2.57  | 160  | 0.3537          |
| 0.3216        | 2.73  | 170  | 0.3423          |
| 0.2859        | 2.89  | 180  | 0.3303          |
| 0.2967        | 3.05  | 190  | 0.3211          |
| 0.2933        | 3.22  | 200  | 0.3114          |
| 0.2716        | 3.38  | 210  | 0.3097          |
| 0.255         | 3.54  | 220  | 0.3053          |
| 0.2731        | 3.7   | 230  | 0.2990          |
| 0.2729        | 3.86  | 240  | 0.2972          |
| 0.2701        | 4.02  | 250  | 0.3030          |
| 0.2558        | 4.18  | 260  | 0.3042          |
| 0.2612        | 4.34  | 270  | 0.3301          |
| 0.3048        | 4.5   | 280  | 0.4564          |
| 0.5437        | 4.66  | 290  | 0.7938          |
| 1.5888        | 4.82  | 300  | 1.5418          |
| 0.6588        | 4.98  | 310  | 0.4630          |
| 0.5345        | 5.14  | 320  | 0.9088          |
| 1.1475        | 5.31  | 330  | 1.6381          |
| 1.6442        | 5.47  | 340  | 2.0495          |
| 2.2517        | 5.63  | 350  | 1.7558          |
| 0.9492        | 5.79  | 360  | 0.5187          |
| 0.3727        | 5.95  | 370  | 0.3763          |
| 0.3139        | 6.11  | 380  | 0.3376          |
| 0.2896        | 6.27  | 390  | 0.3195          |
| 0.283         | 6.43  | 400  | 0.3106          |
| 0.2646        | 6.59  | 410  | 0.3105          |
| 0.2674        | 6.75  | 420  | 0.3256          |
| 0.3482        | 6.91  | 430  | 0.4016          |
| 0.4193        | 7.07  | 440  | 0.6300          |
| 0.7397        | 7.23  | 450  | 1.0617          |
| 1.1954        | 7.4   | 460  | 1.6157          |
| 1.6177        | 7.56  | 470  | 1.8019          |
| 1.2996        | 7.72  | 480  | 0.9151          |
| 0.6605        | 7.88  | 490  | 0.5433          |
| 0.416         | 8.04  | 500  | 0.4012          |
| 0.3412        | 8.2   | 510  | 0.3685          |
| 0.3322        | 8.36  | 520  | 0.3928          |
| 0.3516        | 8.52  | 530  | 0.3641          |
| 0.3406        | 8.68  | 540  | 0.4061          |
| 0.3772        | 8.84  | 550  | 0.4145          |
| 0.3695        | 9.0   | 560  | 0.5453          |
| 0.5824        | 9.16  | 570  | 0.7332          |
| 0.5139        | 9.32  | 580  | 0.4839          |
| 0.3798        | 9.49  | 590  | 0.3758          |
| 0.319         | 9.65  | 600  | 0.3438          |
| 0.3082        | 9.81  | 610  | 0.3301          |
| 0.3017        | 9.97  | 620  | 0.3225          |
| 0.2862        | 10.13 | 630  | 0.3156          |
| 0.2586        | 10.29 | 640  | 0.3109          |
| 0.2878        | 10.45 | 650  | 0.3082          |
| 0.2766        | 10.61 | 660  | 0.3056          |
| 0.2834        | 10.77 | 670  | 0.3042          |
| 0.2513        | 10.93 | 680  | 0.3020          |
| 0.2762        | 11.09 | 690  | 0.3007          |
| 0.28          | 11.25 | 700  | 0.2999          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0