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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-20hrs-v1
    results: []

mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-20hrs-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: 0.2229
  • Cer: 0.0780

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 Cer Val Wer
5.4496 1.0 756 0.1056 0.3067
0.595 2.0 1512 0.0857 0.2488
0.493 3.0 2268 0.0832 0.2436
0.4618 4.0 3024 0.0818 0.2403
0.4422 5.0 3780 0.0809 0.2366
0.4307 6.0 4536 0.0804 0.2359
0.4236 7.0 5292 0.0798 0.2351
0.4153 8.0 6048 0.0796 0.2348
0.4082 9.0 6804 0.0789 0.2329
0.4067 10.0 7560 0.0787 0.2339
0.4002 11.0 8316 0.0784 0.2329
0.3966 12.0 9072 0.0781 0.2328
0.3905 13.0 9828 0.0784 0.2327
0.3865 14.0 10584 0.0778 0.2318
0.3819 15.0 11340 0.0777 0.2320
0.3768 16.0 12096 0.0777 0.2317
0.3716 17.0 12852 0.0770 0.2299
0.3698 18.0 13608 0.0771 0.2284
0.3647 19.0 14364 0.0769 0.2279
0.3651 20.0 15120 0.0769 0.2297
0.361 21.0 15876 0.0769 0.2284
0.3559 22.0 16632 0.0781 0.2298
0.3576 23.0 17388 0.0793 0.2314
0.3486 24.0 18144 0.0761 0.2258
0.3486 25.0 18900 0.0787 0.2304
0.3455 26.0 19656 0.0769 0.2271
0.3451 27.0 20412 0.0767 0.2256
0.3409 28.0 21168 0.0767 0.2247
0.3394 29.0 21924 0.0802 0.2297

Framework versions

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