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kalai_test_model_23_colab
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metadata
license: apache-2.0
base_model: albert/albert-base-v2
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: model_bert_check_new_1
    results: []

model_bert_check_new_1

This model is a fine-tuned version of albert/albert-base-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3250
  • Accuracy: 0.93

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 25 0.5086 0.87
No log 2.0 50 0.3250 0.93

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1