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kadriu
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imja

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: wav2vec2-large-xlsr-53-Total2e-4_4
    results: []

wav2vec2-large-xlsr-53-Total2e-4_4

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2474
  • Wer: 0.1951

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: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
5.5015 0.1 200 2.9261 0.9707
2.9197 0.2 400 2.7757 0.9707
1.7594 0.3 600 0.6117 0.5746
1.0908 0.4 800 0.4673 0.4530
0.9441 0.5 1000 0.4142 0.4010
0.8688 0.6 1200 0.3909 0.3675
0.849 0.7 1400 0.3649 0.3360
0.8223 0.8 1600 0.3532 0.3334
0.821 0.9 1800 0.3513 0.3185
0.7839 1.0 2000 0.3373 0.3039
0.714 1.1 2200 0.3210 0.2922
0.7129 1.2 2400 0.3216 0.2860
0.7076 1.3 2600 0.3279 0.2843
0.73 1.4 2800 0.3111 0.2662
0.7256 1.5 3000 0.3032 0.2625
0.72 1.6 3200 0.3066 0.2571
0.6754 1.7 3400 0.2999 0.2581
0.6859 1.8 3600 0.2935 0.2562
0.6966 1.9 3800 0.2858 0.2469
0.6791 2.0 4000 0.2857 0.2393
0.6412 2.1 4200 0.2815 0.2392
0.6356 2.2 4400 0.2836 0.2343
0.6048 2.3 4600 0.2824 0.2422
0.6473 2.4 4800 0.2805 0.2316
0.659 2.5 5000 0.2775 0.2262
0.6412 2.6 5200 0.2729 0.2249
0.6167 2.7 5400 0.2719 0.2227
0.6226 2.8 5600 0.2661 0.2193
0.6168 2.9 5800 0.2615 0.2172
0.6145 3.0 6000 0.2608 0.2148
0.593 3.1 6200 0.2643 0.2123
0.5919 3.2 6400 0.2617 0.2131
0.6115 3.3 6600 0.2589 0.2114
0.5859 3.4 6800 0.2591 0.2100
0.5919 3.5 7000 0.2564 0.2103
0.5873 3.6 7200 0.2572 0.2074
0.561 3.7 7400 0.2561 0.2056
0.5808 3.8 7600 0.2538 0.2062
0.5701 3.9 7800 0.2517 0.2029
0.5722 4.0 8000 0.2523 0.2007
0.5508 4.1 8200 0.2570 0.2023
0.5591 4.2 8400 0.2502 0.2029
0.5697 4.3 8600 0.2478 0.1991
0.5689 4.4 8800 0.2492 0.2021
0.5345 4.5 9000 0.2498 0.2005
0.5726 4.6 9200 0.2492 0.1983
0.5382 4.7 9400 0.2487 0.1974
0.5614 4.8 9600 0.2481 0.1957
0.5568 4.9 9800 0.2477 0.1955
0.5631 5.0 10000 0.2474 0.1951

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.3
  • Tokenizers 0.10.3