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metadata
base_model: allenai/scibert_scivocab_uncased
tags:
  - generated_from_trainer
model-index:
  - name: scibert_scivocab_uncased-finetuned-molstm-lpm-0.3-25epochs
    results: []

scibert_scivocab_uncased-finetuned-molstm-lpm-0.3-25epochs

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

  • Loss: 0.0407

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: 2e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.1073 1.0 3301 0.0633
0.0657 2.0 6602 0.0563
0.059 3.0 9903 0.0536
0.0556 4.0 13204 0.0518
0.0531 5.0 16505 0.0496
0.0511 6.0 19806 0.0489
0.0498 7.0 23107 0.0477
0.0488 8.0 26408 0.0468
0.0478 9.0 29709 0.0464
0.0467 10.0 33010 0.0455
0.0467 11.0 36311 0.0450
0.0458 12.0 39612 0.0454
0.0449 13.0 42913 0.0441
0.0447 14.0 46214 0.0432
0.044 15.0 49515 0.0428
0.0436 16.0 52816 0.0429
0.0433 17.0 56117 0.0428
0.0431 18.0 59418 0.0423
0.0427 19.0 62719 0.0419
0.0425 20.0 66020 0.0420
0.0422 21.0 69321 0.0412
0.0422 22.0 72622 0.0413
0.0416 23.0 75923 0.0407
0.0415 24.0 79224 0.0410
0.0411 25.0 82525 0.0408

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.0.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2