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: 2.3774
  • Precision: 0.2
  • Recall: 0.0909
  • F1: 0.1250
  • Accuracy: 0.5319

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: 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: 3

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 2 2.8942 0.0 0.0 0.0 0.3830
No log 2.0 4 2.5283 0.0 0.0 0.0 0.4894
No log 3.0 6 2.3774 0.2 0.0909 0.1250 0.5319

Framework versions

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