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odinsynth_encoder_decoder_native_hf_test

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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - enoriega/odinsynth_sequence_dataset
metrics:
  - accuracy
model-index:
  - name: odinsynth_encoder_decoder_native_hf_test
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: enoriega/odinsynth_sequence_dataset synthetic_surface
          type: enoriega/odinsynth_sequence_dataset
          config: synthetic_surface
          split: validation
          args: synthetic_surface
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9332402379440391

odinsynth_encoder_decoder_native_hf_test

This model is a fine-tuned version of bert-base-uncased on the enoriega/odinsynth_sequence_dataset synthetic_surface dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0533
  • Accuracy: 0.9332

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: 3
  • eval_batch_size: 3
  • seed: 42
  • gradient_accumulation_steps: 200
  • total_train_batch_size: 600
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
6.5753 0.67 60 6.1666 0.0150
2.5262 1.34 120 2.1713 0.9345
0.2343 2.01 180 0.1787 0.9346
0.0713 2.68 240 0.0686 0.9330
0.0631 3.35 300 0.0621 0.9334
0.0603 4.02 360 0.0594 0.9332
0.0589 4.69 420 0.0583 0.9334
0.0579 5.36 480 0.0572 0.9336
0.0575 6.03 540 0.0566 0.9333
0.0561 6.69 600 0.0562 0.9333
0.0559 7.36 660 0.0559 0.9332
0.0551 8.03 720 0.0556 0.9332
0.0548 8.7 780 0.0552 0.9333
0.0546 9.37 840 0.0550 0.9333
0.0539 10.04 900 0.0547 0.9331
0.0546 10.71 960 0.0544 0.9332
0.0538 11.38 1020 0.0543 0.9335
0.0534 12.05 1080 0.0540 0.9333
0.0532 12.72 1140 0.0539 0.9334
0.0525 13.39 1200 0.0538 0.9334
0.0526 14.06 1260 0.0538 0.9331
0.0527 14.73 1320 0.0536 0.9331
0.0529 15.4 1380 0.0536 0.9331
0.0526 16.07 1440 0.0535 0.9331
0.0524 16.74 1500 0.0534 0.9333
0.0516 17.41 1560 0.0534 0.9331
0.0527 18.08 1620 0.0534 0.9332
0.0521 18.74 1680 0.0533 0.9332
0.0519 19.41 1740 0.0533 0.9332

Framework versions

  • Transformers 4.27.4
  • Pytorch 2.0.0
  • Datasets 2.11.0
  • Tokenizers 0.11.0