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vericava/qwen3-0.6b-vericava-posts-v1

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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qwen3-0.6b-vericava-posts-v1

This is a model trained from scratch, using parameters of Qwen/Qwen3-0.6B-FP8 on a dataset of my posts on the Internet.

It achieves the following results on the evaluation set:

  • —Loss: 6.8017

Model description

It generates text resembling what I post on the Internet.

Intended uses & limitations

CAUTION: It may produce something I'd never say.

I do not impose any restriction(s) on the use of this model.

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 0.0005
  • —trainbatchsize: 128
  • —evalbatchsize: 128
  • —seed: 42
  • —gradientaccumulationsteps: 8
  • —totaltrainbatch_size: 1024
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 1000
  • —num_epochs: 100

Training results

Training LossEpochStepValidation Loss
2.484511.12311007.7641
1.722.24622006.2579
1.417933.36923005.6225
1.252144.49234005.4497
1.090555.61545005.5389
0.838266.73856005.9830
0.551177.86157006.3376
0.336488.98468006.5791
0.2083100.09006.8017

Framework versions

  • —Transformers 4.52.4
  • —Pytorch 2.6.0+cu124
  • —Datasets 3.6.0
  • —Tokenizers 0.21.1