anton-l's picture
anton-l HF staff
update model card README.md
89032ef
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - xtreme_s
metrics:
  - f1
  - accuracy
model-index:
  - name: xtreme_s_xlsr_300m_minds14_resplit
    results: []

xtreme_s_xlsr_300m_minds14_resplit

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: 0.3826
  • F1: 0.9106
  • Accuracy: 0.9103

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: 32
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1500
  • num_epochs: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Accuracy
2.6739 5.41 200 2.5687 0.0430 0.1190
1.4953 10.81 400 1.6052 0.5550 0.5692
0.6177 16.22 600 0.7927 0.8052 0.8011
0.3609 21.62 800 0.5679 0.8609 0.8609
0.4972 27.03 1000 0.5944 0.8509 0.8523
0.1799 32.43 1200 0.6194 0.8623 0.8621
0.1308 37.84 1400 0.5956 0.8569 0.8548
0.2298 43.24 1600 0.5201 0.8732 0.8743
0.0052 48.65 1800 0.3826 0.9106 0.9103

Framework versions

  • Transformers 4.18.0.dev0
  • Pytorch 1.10.2+cu113
  • Datasets 2.0.1.dev0
  • Tokenizers 0.11.6