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End of training
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metadata
base_model: gokuls/model_v1_complete_training_wt_init_48_tiny
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: hbertv1-tiny-wt-48-emotion
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          config: split
          split: validation
          args: split
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8985

hbertv1-tiny-wt-48-emotion

This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_tiny on the emotion dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2695
  • Accuracy: 0.8985

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: 33
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.4321 1.0 250 1.0203 0.6475
0.8329 2.0 500 0.5954 0.814
0.5347 3.0 750 0.4146 0.8645
0.398 4.0 1000 0.3496 0.8805
0.3418 5.0 1250 0.3091 0.889
0.2932 6.0 1500 0.2864 0.8945
0.2646 7.0 1750 0.2782 0.8965
0.2532 8.0 2000 0.2695 0.8985
0.2342 9.0 2250 0.2632 0.898
0.225 10.0 2500 0.2617 0.897

Framework versions

  • Transformers 4.31.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.13.1
  • Tokenizers 0.13.3