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roberta-base-fine-tuned-text-classificarion-ds-ss-customLoss
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metadata
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-bne
tags:
  - generated_from_trainer
metrics:
  - f1
  - recall
  - accuracy
  - precision
model-index:
  - name: roberta-base-fine-tuned-text-classificarion-ds-ss2
    results: []

roberta-base-fine-tuned-text-classificarion-ds-ss2

This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1475
  • F1: 0.7875
  • Recall: 0.7818
  • Accuracy: 0.7818
  • Precision: 0.8021

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
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss F1 Recall Accuracy Precision
No log 1.0 442 0.9007 0.7765 0.7793 0.7793 0.7882
0.8538 2.0 884 0.9423 0.7772 0.7751 0.7751 0.7954
0.352 3.0 1326 0.9751 0.7842 0.7846 0.7846 0.7899
0.1244 4.0 1768 1.0226 0.7972 0.7970 0.7970 0.8019
0.046 5.0 2210 1.1475 0.7875 0.7818 0.7818 0.8021

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3