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metadata
license: cc-by-nc-3.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
base_model: QCRI/bert-base-multilingual-cased-pos-english
model-index:
  - name: finetuning-sentiment-model-bert-multilingual
    results: []

finetuning-sentiment-model-bert-multilingual

This model is a fine-tuned version of QCRI/bert-base-multilingual-cased-pos-english on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.9412
  • Accuracy: 0.6624
  • F1: 0.6624
  • Precision: 0.6624
  • Recall: 0.6624

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: 10

Training results

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.6.1
  • Tokenizers 0.13.2