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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: fb-data2vec-finetuned-finance-classification
    results: []

fb-data2vec-finetuned-finance-classification

This model is a fine-tuned version of facebook/data2vec-text-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8993
  • Accuracy: 0.8557
  • F1: 0.8563
  • Precision: 0.8576
  • Recall: 0.8557

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: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
No log 1.0 285 0.6704 0.6680 0.6262 0.7919 0.6680
0.6626 2.0 570 0.4731 0.8360 0.8350 0.8346 0.8360
0.6626 3.0 855 0.4598 0.8458 0.8454 0.8452 0.8458
0.3666 4.0 1140 0.4758 0.8360 0.8352 0.8353 0.8360
0.3666 5.0 1425 0.5683 0.8340 0.8342 0.8353 0.8340
0.2316 6.0 1710 0.6234 0.8419 0.8421 0.8447 0.8419
0.2316 7.0 1995 0.7186 0.8379 0.8385 0.8395 0.8379
0.1523 8.0 2280 0.7268 0.8439 0.8442 0.8455 0.8439
0.0928 9.0 2565 0.7364 0.8439 0.8452 0.8494 0.8439
0.0928 10.0 2850 0.7975 0.8478 0.8476 0.8476 0.8478
0.054 11.0 3135 0.9019 0.8498 0.8509 0.8554 0.8498
0.054 12.0 3420 0.8779 0.8538 0.8548 0.8578 0.8538
0.036 13.0 3705 0.8914 0.8617 0.8626 0.8652 0.8617
0.036 14.0 3990 0.8976 0.8538 0.8547 0.8572 0.8538
0.0232 15.0 4275 0.8993 0.8557 0.8563 0.8576 0.8557

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0+cu113
  • Datasets 2.1.0
  • Tokenizers 0.12.1