Hugging Face's logo

onuralp
/
Mistral-7B-v0.1-QLoRA-01

Text Generation
Transformers
llama
Generated from Trainer
Inference Endpoints
4-bit precision
bitsandbytes
Model card Files Community
Mistral-7B-v0.1-QLoRA-01 / README.md
onuralp's picture
onuralp
Upload folder using huggingface_hub
482e863
preview code
|
raw
history blame contribute delete
4.1 kB
metadata
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
  - generated_from_trainer
model-index:
  - name: qlora-out
    results: []

Built with Axolotl

qlora-out

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5631

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: 0.0004
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 300
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
0.8335 0.06 20 0.6429
0.6725 0.12 40 0.5888
0.5927 0.18 60 0.5603
0.5847 0.24 80 0.5362
0.5552 0.3 100 0.5256
0.5511 0.36 120 0.5243
0.5466 0.42 140 0.5102
0.4395 0.48 160 0.5065
0.6854 0.54 180 0.4971
0.7326 0.6 200 0.5150
0.8204 0.66 220 0.5008
0.6009 0.72 240 0.4972
0.4471 0.78 260 0.4944
0.5934 0.84 280 0.5146
0.6574 0.9 300 0.5057
0.4566 0.96 320 0.4880
0.6119 1.02 340 0.5442
0.3779 1.08 360 0.5540
0.4431 1.14 380 0.5375
0.38 1.2 400 0.5541
0.4542 1.26 420 0.5359
0.5392 1.32 440 0.5394
0.2573 1.38 460 0.5318
0.5441 1.44 480 0.5201
0.3758 1.5 500 0.5147
0.4403 1.56 520 0.5134
0.3308 1.62 540 0.5289
0.4604 1.68 560 0.5205
0.4479 1.74 580 0.5340
0.521 1.8 600 0.5094
0.32 1.86 620 0.4995
0.3984 1.92 640 0.4878
0.3799 1.98 660 0.4826
0.1484 2.04 680 0.7261
0.3305 2.1 700 0.6187
0.1477 2.16 720 0.5499
0.176 2.22 740 0.5796
0.1892 2.28 760 0.5717
0.1921 2.34 780 0.5416
0.1366 2.4 800 0.5866
0.1726 2.46 820 0.5562
0.1264 2.51 840 0.5621
0.2054 2.57 860 0.5678
0.1722 2.63 880 0.5573
0.2399 2.69 900 0.5553
0.229 2.75 920 0.5565
0.1876 2.81 940 0.5609
0.2281 2.87 960 0.5633
0.1727 2.93 980 0.5645
0.3536 2.99 1000 0.5631

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1