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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: sentiment-10Epochs-2-work-please
    results: []

sentiment-10Epochs-2-work-please

This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7450
  • Accuracy: 0.8549
  • F1: 0.8516
  • Precision: 0.8714
  • Recall: 0.8327

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: 8
  • eval_batch_size: 8
  • seed: 42
  • 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 F1 Precision Recall
0.3685 1.0 7088 0.4334 0.8590 0.8463 0.9304 0.7762
0.3721 2.0 14176 0.3822 0.8673 0.8575 0.9257 0.7987
0.3393 3.0 21264 0.4634 0.8705 0.8619 0.9228 0.8086
0.3017 4.0 28352 0.4806 0.8708 0.8630 0.9186 0.8137
0.3072 5.0 35440 0.4509 0.87 0.8648 0.9009 0.8314
0.2833 6.0 42528 0.5339 0.8627 0.8581 0.8879 0.8302
0.2633 7.0 49616 0.5457 0.8637 0.8614 0.8759 0.8473
0.2418 8.0 56704 0.6408 0.8589 0.8563 0.8722 0.8410
0.1999 9.0 63792 0.7404 0.8530 0.8485 0.8752 0.8235
0.1809 10.0 70880 0.7450 0.8549 0.8516 0.8714 0.8327

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.10.0
  • Datasets 2.0.0
  • Tokenizers 0.11.6