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trained model on the new 8-iterations clean data
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metadata
base_model: UBC-NLP/MARBERT
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: marbert-finetuned-wanlp_sarcasm
    results: []

marbert-finetuned-wanlp_sarcasm

This model is a fine-tuned version of UBC-NLP/MARBERT on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6362
  • Accuracy: 0.9485
  • Precision: 0.7758
  • Recall: 0.7814
  • F1: 0.7786

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.2904 1.0 226 0.4947 0.9402 0.8199 0.6201 0.7061
0.2199 2.0 452 0.4060 0.9406 0.7345 0.7634 0.7487
0.0545 3.0 678 0.6362 0.9485 0.7758 0.7814 0.7786

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1