emotion-classifier / README.md
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metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
  - generated_from_trainer
model-index:
  - name: outputs
    results: []

outputs

This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1671
  • Pearson: 0.8847

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: 8e-05
  • train_batch_size: 256
  • eval_batch_size: 512
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Pearson
No log 1.0 18 0.6667 0.1236
No log 2.0 36 0.4215 0.6237
No log 3.0 54 0.3060 0.8074
No log 4.0 72 0.1798 0.8774
No log 5.0 90 0.1671 0.8847

Framework versions

  • Transformers 4.33.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3