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mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-10hrs-v1

Automatic Speech Recognition
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wav2vec2
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metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-10hrs-v1
    results: []

mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-10hrs-v1

This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:

  • Wer: 0.2298
  • Cer: 0.0792

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Val Wer Val Cer
6.1301 1.0 367 0.3014 0.1016
0.706 2.0 734 0.2576 0.0893
0.6107 3.0 1101 0.2494 0.0863
0.5664 4.0 1468 0.2467 0.0848
0.5353 5.0 1835 0.2430 0.0836
0.5086 6.0 2202 0.2414 0.0830
0.4963 7.0 2569 0.2404 0.0822
0.4773 8.0 2936 0.2391 0.0817
0.4619 9.0 3303 0.2396 0.0814
0.4566 10.0 3670 0.2379 0.0810
0.4474 11.0 4037 0.2376 0.0807
0.4356 12.0 4404 0.2374 0.0804
0.4331 13.0 4771 0.2361 0.0801
0.4297 14.0 5138 0.2364 0.0800
0.4219 15.0 5505 0.2356 0.0798
0.4067 16.0 5872 0.2341 0.0793
0.4158 17.0 6239 0.2348 0.0792
0.4071 18.0 6606 0.2337 0.0788
0.4018 19.0 6973 0.2334 0.0787
0.3907 20.0 7340 0.2329 0.0787
0.3937 21.0 7707 0.2318 0.0784
0.3895 22.0 8074 0.2329 0.0787
0.3851 23.0 8441 0.2322 0.0784
0.3844 24.0 8808 0.2313 0.0780
0.3799 25.0 9175 0.2333 0.0791
0.3754 26.0 9542 0.2344 0.0794
0.3733 27.0 9909 0.2290 0.0779
0.3761 28.0 10276 0.2321 0.0793
0.3678 29.0 10643 0.2329 0.0789
0.3639 30.0 11010 0.2327 0.0795
0.361 31.0 11377 0.2313 0.0791
0.3559 32.0 11744 0.2303 0.0788
0.3596 33.0 12111 0.2310 0.0797
0.358 34.0 12478 0.2422 0.0874
0.3501 35.0 12845 0.2309 0.0802
0.3533 36.0 13212 0.2293 0.0793
0.349 37.0 13579 0.2298 0.0792

Framework versions

  • Transformers 4.48.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0