my_model / README.md
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metadata
license: apache-2.0
base_model: PartAI/TookaBERT-Base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: my_model
    results: []

my_model

This model is a fine-tuned version of PartAI/TookaBERT-Base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9495
  • Precision: 0.5098
  • Recall: 0.4866
  • F1: 0.4979
  • Accuracy: 0.8050

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 10 1.4199 0.3919 0.3102 0.3463 0.7206
No log 2.0 20 1.2065 0.4497 0.3824 0.4133 0.7573
No log 3.0 30 1.0512 0.4792 0.4305 0.4535 0.7759
No log 4.0 40 0.9780 0.5056 0.4840 0.4945 0.8022
No log 5.0 50 0.9495 0.5098 0.4866 0.4979 0.8050

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1