gayanin/pubmed-mixed-noise-v3-0.2

Source: 🤗apache-2.0139M params558 MBsafetensors✓ 6 checksumsupdated 995d ago
or submit a torrent

pubmed-mixed-noise-v3-0.2

This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4140

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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.7328 0.11 500 0.6952
0.6994 0.21 1000 0.6005
0.6684 0.32 1500 0.5670
0.6305 0.43 2000 0.5402
0.6224 0.54 2500 0.5175
0.6009 0.64 3000 0.5001
0.5126 0.75 3500 0.4935
0.5698 0.86 4000 0.4793
0.497 0.96 4500 0.4715
0.3716 1.07 5000 0.4689
0.4522 1.18 5500 0.4551
0.3958 1.28 6000 0.4556
0.4398 1.39 6500 0.4502
0.4572 1.5 7000 0.4425
0.4339 1.61 7500 0.4424
0.4289 1.71 8000 0.4322
0.3771 1.82 8500 0.4337
0.3668 1.93 9000 0.4265
0.3342 2.03 9500 0.4316
0.3465 2.14 10000 0.4244
0.32 2.25 10500 0.4226
0.3493 2.35 11000 0.4244
0.3549 2.46 11500 0.4216
0.3281 2.57 12000 0.4192
0.3259 2.68 12500 0.4181
0.3444 2.78 13000 0.4156
0.3201 2.89 13500 0.4146
0.3315 3.0 14000 0.4140

Framework versions

  • Transformers 4.36.1
  • Pytorch 2.0.1
  • Datasets 2.16.1
  • Tokenizers 0.15.0