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xls-r-1b-bem-genbed-f-model

Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
genbed
Generated from Trainer
Inference Endpoints
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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
  - automatic-speech-recognition
  - genbed
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: xls-r-1b-bem-genbed-f-model
    results: []

xls-r-1b-bem-genbed-f-model

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the GENBED - BEM dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3137
  • Wer: 0.5529

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: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 30.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.2740 100 3.0378 1.0
No log 0.5479 200 0.8302 0.9818
No log 0.8219 300 0.6783 0.9103
No log 1.0959 400 0.5512 0.8721
1.8782 1.3699 500 0.5296 0.8568
1.8782 1.6438 600 0.4413 0.7333
1.8782 1.9178 700 0.4747 0.7614
1.8782 2.1918 800 0.3884 0.6667
1.8782 2.4658 900 0.3577 0.6355
0.5114 2.7397 1000 0.3585 0.6321
0.5114 3.0137 1100 0.3641 0.6607
0.5114 3.2877 1200 0.3813 0.7282
0.5114 3.5616 1300 0.3829 0.7086
0.5114 3.8356 1400 0.3682 0.6413
0.3931 4.1096 1500 0.3527 0.6221
0.3931 4.3836 1600 0.3481 0.6297
0.3931 4.6575 1700 0.3541 0.6193
0.3931 4.9315 1800 0.3355 0.6242
0.3931 5.2055 1900 0.3339 0.5801
0.3293 5.4795 2000 0.3137 0.5529
0.3293 5.7534 2100 0.3132 0.5822
0.3293 6.0274 2200 0.3145 0.5676
0.3293 6.3014 2300 0.3283 0.5961
0.3293 6.5753 2400 0.3247 0.5988

Framework versions

  • Transformers 4.46.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0