CoolFace
Modelpublic

NasimB/gpt2-concat-all-mod-datasets1-rarity-all-iorder-end-c2p6k

sourceHugging Facemitupdated 3y agoView on Hugging Face
0likes18downloads
Model Card

<!-- 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. -->

gpt2-concat-all-mod-datasets1-rarity-all-iorder-end-c2p6k

This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:

  • —Loss: 4.3830

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: 0.0005
  • —trainbatchsize: 64
  • —evalbatchsize: 64
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 1000
  • —num_epochs: 6
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
6.7840.325005.6510
5.44580.6310005.2234
5.09990.9515004.9802
4.80391.2620004.8338
4.67121.5825004.7110
4.56431.8930004.5978
4.34992.2135004.5524
4.25382.5240004.4816
4.22022.8445004.4235
4.06293.1550004.4144
3.93413.4755004.3803
3.91863.7860004.3457
3.80844.165004.3452
3.63434.4170004.3378
3.63174.7375004.3197
3.59475.0480004.3232
3.43695.3685004.3272
3.4345.6790004.3271
3.43275.9995004.3265

Framework versions

  • —Transformers 4.26.1
  • —Pytorch 1.11.0+cu113
  • —Datasets 2.13.0
  • —Tokenizers 0.13.3