HODravidianLangTech / README.md
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metadata
license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: HODravidianLangTech
    results: []

HODravidianLangTech

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: 0.5859
  • F1: 0.6908

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: 1e-06
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 1234
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 100 0.6926 0.3377
No log 2.0 200 0.6916 0.5490
No log 3.0 300 0.6856 0.6050
No log 4.0 400 0.6701 0.6287
0.6833 5.0 500 0.6601 0.6396
0.6833 6.0 600 0.6511 0.6466
0.6833 7.0 700 0.6447 0.6458
0.6833 8.0 800 0.6250 0.6560
0.6833 9.0 900 0.6113 0.6516
0.624 10.0 1000 0.6051 0.6658
0.624 11.0 1100 0.6075 0.6567
0.624 12.0 1200 0.6038 0.6671
0.624 13.0 1300 0.5997 0.6716
0.624 14.0 1400 0.5949 0.6805
0.5739 15.0 1500 0.5958 0.6885
0.5739 16.0 1600 0.5924 0.6905
0.5739 17.0 1700 0.5957 0.6875
0.5739 18.0 1800 0.5839 0.6976
0.5739 19.0 1900 0.5865 0.6908
0.5598 20.0 2000 0.5859 0.6908

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0