vericava/qwen3-1.7b-vericava-posts-v1
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qwen3-1.7b-vericava-posts-v1
This is a model trained from scratch, using parameters of Qwen/Qwen3-1.7B on a dataset of my posts on the Internet.
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: 0.0002
- trainbatchsize: 8
- evalbatchsize: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradientaccumulationsteps: 8
- totaltrainbatch_size: 256
- totalevalbatch_size: 32
- optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
- lrschedulertype: cosine
- lrschedulerwarmup_steps: 300
- num_epochs: 400
Training results
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
