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scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta / 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-cl-cardiff_cl_only_beta
    results: []

scenario-TCR-XLMV_data-cl-cardiff_cl_only_beta

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: 112233
  • 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 1.09 250 1.0993 0.3333 0.1667
1.1009 2.17 500 1.0989 0.3333 0.1667
1.1009 3.26 750 1.0998 0.3333 0.1667
1.0998 4.35 1000 1.0991 0.3333 0.1667
1.0998 5.43 1250 1.0987 0.3333 0.1667
1.1003 6.52 1500 1.0991 0.3333 0.1667
1.1003 7.61 1750 1.0999 0.3333 0.1667
1.1001 8.7 2000 1.0988 0.3333 0.1667
1.1001 9.78 2250 1.0986 0.3333 0.1667
1.0996 10.87 2500 1.0989 0.3333 0.1667
1.0996 11.96 2750 1.0989 0.3333 0.1667
1.1001 13.04 3000 1.0986 0.3333 0.1667
1.1001 14.13 3250 1.0994 0.3333 0.1667
1.0981 15.22 3500 1.1405 0.3333 0.1667
1.0981 16.3 3750 1.0987 0.3333 0.1667
1.0993 17.39 4000 1.0987 0.3333 0.1667
1.0993 18.48 4250 1.0990 0.3333 0.1667
1.0987 19.57 4500 1.0978 0.3457 0.2853
1.0987 20.65 4750 1.0999 0.3380 0.2148
1.0943 21.74 5000 1.0987 0.3333 0.1667
1.0943 22.83 5250 1.0987 0.3333 0.1667
1.0991 23.91 5500 1.0986 0.3333 0.1667
1.0991 25.0 5750 1.0986 0.3333 0.1667
1.0988 26.09 6000 1.0986 0.3333 0.1667
1.0988 27.17 6250 1.0986 0.3333 0.1667
1.0991 28.26 6500 1.0986 0.3333 0.1667
1.0991 29.35 6750 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