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scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma

Text Classification
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PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma / README.md
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metadata
license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma
    results: []

scenario-NON-KD-PR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only_gamma

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

  • Loss: 5.4088
  • Accuracy: 0.4452
  • F1: 0.4432

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: 11423
  • 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 1.1861 0.4599 0.4461
0.8893 2.17 500 1.2483 0.4753 0.4682
0.8893 3.26 750 1.4640 0.4877 0.4872
0.5435 4.35 1000 1.9901 0.4529 0.4440
0.5435 5.43 1250 2.1858 0.4398 0.4357
0.2767 6.52 1500 2.2484 0.4653 0.4643
0.2767 7.61 1750 2.7287 0.4653 0.4642
0.1584 8.7 2000 2.7996 0.4637 0.4616
0.1584 9.78 2250 3.2599 0.4684 0.4684
0.1119 10.87 2500 3.7690 0.4344 0.4244
0.1119 11.96 2750 3.5578 0.4591 0.4584
0.0771 13.04 3000 3.9089 0.4483 0.4490
0.0771 14.13 3250 4.1349 0.4637 0.4587
0.054 15.22 3500 4.4418 0.4506 0.4435
0.054 16.3 3750 4.4987 0.4522 0.4511
0.04 17.39 4000 4.5234 0.4514 0.4511
0.04 18.48 4250 4.7455 0.4529 0.4517
0.0241 19.57 4500 5.0606 0.4329 0.4238
0.0241 20.65 4750 5.0820 0.4414 0.4394
0.0243 21.74 5000 5.2753 0.4360 0.4304
0.0243 22.83 5250 5.1224 0.4660 0.4666
0.0155 23.91 5500 5.2712 0.4437 0.4407
0.0155 25.0 5750 5.3846 0.4421 0.4393
0.0156 26.09 6000 5.4060 0.4398 0.4352
0.0156 27.17 6250 5.3914 0.4383 0.4344
0.0105 28.26 6500 5.3427 0.4421 0.4413
0.0105 29.35 6750 5.4088 0.4452 0.4432

Framework versions

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