CoolFace
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AhmedZaky1/authorship_model

sourceHugging Faceapache-2.0updated 4mo agoView on Hugging Face
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Model Card

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authorship_model

This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the authorship_train dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4835

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
  • trainbatchsize: 1
  • evalbatchsize: 1
  • seed: 42
  • gradientaccumulationsteps: 8
  • totaltrainbatch_size: 8
  • optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lrschedulertype: cosine
  • lrschedulerwarmup_steps: 20
  • num_epochs: 3.0
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
1.33470.05285000.6354
1.31940.105710000.6109
1.20270.158515000.5906
1.23600.211420000.5835
1.26720.264225000.5752
1.16660.317130000.5580
1.15430.369935000.5537
1.19330.422740000.5499
1.20750.475645000.5418
1.06870.528450000.5443
1.03090.581355000.5371
0.94160.634160000.5339
1.17050.686965000.5248
0.90560.739870000.5215
1.07910.792675000.5182
1.00820.845580000.5137
1.13000.898385000.5123
1.08040.951290000.5095
0.92951.003995000.5073
0.99951.0568100000.5065
1.04301.1096105000.5050
1.07541.1624110000.5025
1.02581.2153115000.5010
1.07201.2681120000.4990
1.01411.3210125000.4977
0.91021.3738130000.4960
1.03011.4266135000.4951
0.89901.4795140000.4934
1.00461.5323145000.4922
0.87611.5852150000.4909
1.04351.6380155000.4897
0.97031.6909160000.4875
0.89011.7437165000.4857
0.95231.7965170000.4855
0.96631.8494175000.4838
0.97411.9022180000.4831
0.96861.9551185000.4817
0.82082.0078190000.4860
0.90672.0607195000.4867
0.89432.1135200000.4873
0.92042.1663205000.4863
0.83432.2192210000.4863
0.85422.2720215000.4871
0.91982.3249220000.4863
0.87542.3777225000.4859
0.86452.4306230000.4852
0.85002.4834235000.4841
0.86992.5362240000.4842
0.84492.5891245000.4841
0.85932.6419250000.4841
0.79192.6948255000.4837
0.77072.7476260000.4841
0.83062.8005265000.4839
0.79692.8533270000.4837
0.92312.9061275000.4837
0.91092.9590280000.4836

Framework versions

  • PEFT 0.18.1
  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2