fine_tuned_emBERT / README.md
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metadata
license: apache-2.0
base_model: morten-j/Mehdie_Extended-mBERT
tags:
  - generated_from_trainer
metrics:
  - f1
  - precision
  - recall
model-index:
  - name: fine_tuned_emBERT
    results: []

fine_tuned_emBERT

This model is a fine-tuned version of morten-j/Mehdie_Extended-mBERT on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2085
  • F1: 0.6316
  • F5: 0.6072
  • Precision: 0.7059
  • Recall: 0.5714

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.2
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 F5 Precision Recall
No log 1.0 38 0.2641 0.0 0.0 0.0 0.0
No log 2.0 76 0.2444 0.0 0.0 0.0 0.0
No log 3.0 114 0.2411 0.0 0.0 0.0 0.0
No log 4.0 152 0.2419 0.0 0.0 0.0 0.0
No log 5.0 190 0.1799 0.4375 0.3994 0.5833 0.35
No log 6.0 228 0.2493 0.4444 0.4641 0.4 0.5
No log 7.0 266 0.2708 0.4444 0.4641 0.4 0.5
No log 8.0 304 0.2356 0.5517 0.4819 0.8889 0.4
No log 9.0 342 0.2139 0.5333 0.4731 0.8 0.4
No log 10.0 380 0.2477 0.4444 0.3754 0.8571 0.3

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2