your_output_dir

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

  • Loss: nan

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: 0.001
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 120000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.217 0.0833 10000 nan
1.1568 0.1667 20000 nan
1.1522 0.25 30000 nan
1.1443 0.3333 40000 nan
1.1404 0.4167 50000 nan
1.1329 0.5 60000 nan
1.1323 0.5833 70000 nan
1.1292 0.6667 80000 nan
1.1264 0.75 90000 nan
1.1312 0.8333 100000 nan
1.1305 0.9167 110000 nan
1.1285 1.0 120000 nan

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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Dataset used to train ottomoritz/TriboliumGPN