Emotion_Albert / README.md
elyadenysova's picture
End of training
7943f2c verified
metadata
license: apache-2.0
base_model: albert-base-v2
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: Emotion_Albert
    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: 0.9295

Emotion_Albert

This model is a fine-tuned version of albert-base-v2 on the emotion dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1537
  • Accuracy: 0.9295

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: 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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3094 1.0 1000 0.2669 0.9145
0.1776 2.0 2000 0.2013 0.928
0.1129 3.0 3000 0.1541 0.936

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2