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scenario-TCR-XLMV_data-en-cardiff_eng_only_beta2

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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scenario-TCR-XLMV_data-en-cardiff_eng_only_beta2 / README.md
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metadata
license: mit
base_model: facebook/xlm-v-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: scenario-TCR-XLMV_data-en-cardiff_eng_only_beta2
    results: []

scenario-TCR-XLMV_data-en-cardiff_eng_only_beta2

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

  • Loss: 1.0986
  • Accuracy: 0.3333
  • F1: 0.1667

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 67
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.03 60 1.0981 0.3677 0.3195
No log 2.07 120 1.0990 0.3333 0.1667
No log 3.1 180 1.0989 0.3333 0.1667
No log 4.14 240 1.0987 0.3333 0.1667
No log 5.17 300 1.0986 0.3333 0.1667
No log 6.21 360 1.0989 0.3333 0.1667
No log 7.24 420 1.0992 0.3333 0.1667
No log 8.28 480 1.0986 0.3333 0.1667
1.1002 9.31 540 1.0994 0.3333 0.1667
1.1002 10.34 600 1.0987 0.3333 0.1667
1.1002 11.38 660 1.0986 0.3333 0.1667
1.1002 12.41 720 1.0987 0.3333 0.1667
1.1002 13.45 780 1.0987 0.3333 0.1667
1.1002 14.48 840 1.0987 0.3333 0.1667
1.1002 15.52 900 1.0991 0.3333 0.1667
1.1002 16.55 960 1.0988 0.3333 0.1667
1.1 17.59 1020 1.0987 0.3333 0.1667
1.1 18.62 1080 1.0987 0.3333 0.1667
1.1 19.66 1140 1.0988 0.3333 0.1667
1.1 20.69 1200 1.0987 0.3333 0.1667
1.1 21.72 1260 1.0987 0.3333 0.1667
1.1 22.76 1320 1.0986 0.3333 0.1667
1.1 23.79 1380 1.0987 0.3333 0.1667
1.1 24.83 1440 1.0986 0.3333 0.1667
1.0989 25.86 1500 1.0986 0.3333 0.1667
1.0989 26.9 1560 1.0986 0.3333 0.1667
1.0989 27.93 1620 1.0986 0.3333 0.1667
1.0989 28.97 1680 1.0986 0.3333 0.1667
1.0989 30.0 1740 1.0986 0.3333 0.1667

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.1.1+cu121
  • Datasets 2.14.5
  • Tokenizers 0.13.3