memobert3_ED2 / README.md
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metadata
library_name: transformers
base_model: MiMe-MeMo/MeMo-BERT-03
tags:
  - generated_from_trainer
model-index:
  - name: memobert3_ED1
    results: []

memobert3_ED1

This model is a fine-tuned version of MiMe-MeMo/MeMo-BERT-03 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6065
  • F1-score: 0.9098

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss F1-score
No log 1.0 69 0.3808 0.8439
No log 2.0 138 0.4234 0.8432
No log 3.0 207 0.4577 0.9013
No log 4.0 276 0.6278 0.8851
No log 5.0 345 0.6449 0.8517
No log 6.0 414 0.7495 0.8678
No log 7.0 483 0.6065 0.9098
0.1663 8.0 552 0.6217 0.9098
0.1663 9.0 621 0.6420 0.9098
0.1663 10.0 690 0.6514 0.9098
0.1663 11.0 759 0.6627 0.9098
0.1663 12.0 828 0.6726 0.9098
0.1663 13.0 897 0.6828 0.9016
0.1663 14.0 966 0.6904 0.9016
0.0001 15.0 1035 0.6942 0.9016
0.0001 16.0 1104 0.6976 0.9016
0.0001 17.0 1173 0.7007 0.9016
0.0001 18.0 1242 0.7027 0.9016
0.0001 19.0 1311 0.7038 0.9016
0.0001 20.0 1380 0.7037 0.9016

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1