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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - xtreme_s
metrics:
  - accuracy
model-index:
  - name: xtreme_s_xlsr_300m_fleurs_langid_truncated
    results: []

xtreme_s_xlsr_300m_fleurs_langid_truncated

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the xtreme_s dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3514
  • Accuracy: 0.7236

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: 0.0003
  • train_batch_size: 4
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 5.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5296 0.26 1000 2.6633 0.4016
0.4252 0.52 2000 1.8582 0.5751
0.2989 0.78 3000 1.6780 0.6332
0.3563 1.04 4000 1.4479 0.6799
0.1617 1.3 5000 1.5066 0.6679
0.1409 1.56 6000 1.4082 0.6992
0.01 1.82 7000 1.2448 0.7071
0.0018 2.08 8000 1.1996 0.7148
0.0014 2.34 9000 1.6505 0.6410
0.0188 2.6 10000 1.4050 0.6840
0.0007 2.86 11000 1.5831 0.6621
0.1038 3.12 12000 1.5441 0.6829
0.0003 3.38 13000 1.3483 0.6900
0.0004 3.64 14000 1.7070 0.6414
0.0003 3.9 15000 1.3198 0.7075
0.0002 4.16 16000 1.3118 0.7105
0.0001 4.42 17000 1.4099 0.7029
0.0 4.68 18000 1.3658 0.7180
0.0001 4.93 19000 1.3514 0.7236

Framework versions

  • Transformers 4.18.0.dev0
  • Pytorch 1.11.0+cu113
  • Datasets 1.18.4.dev0
  • Tokenizers 0.11.6