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mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-5hrs-v1

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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-5hrs-v1
    results: []

mms-1b-all-sw-CV_Fleurs_AMMI_ALFFA-5hrs-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: 0.2369
  • Cer: 0.0801

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
9.5784 1.0 183 0.9998 0.9646
1.9211 2.0 366 0.2887 0.0983
0.6977 3.0 549 0.2641 0.0915
0.6391 4.0 732 0.2568 0.0893
0.59 5.0 915 0.2502 0.0874
0.5654 6.0 1098 0.2489 0.0865
0.5544 7.0 1281 0.2459 0.0853
0.5385 8.0 1464 0.2443 0.0846
0.5256 9.0 1647 0.2442 0.0841
0.5152 10.0 1830 0.2420 0.0837
0.5116 11.0 2013 0.2411 0.0833
0.497 12.0 2196 0.2414 0.0829
0.4969 13.0 2379 0.2400 0.0826
0.4887 14.0 2562 0.2396 0.0824
0.4849 15.0 2745 0.2394 0.0820
0.473 16.0 2928 0.2396 0.0820
0.4732 17.0 3111 0.2403 0.0819
0.4648 18.0 3294 0.2396 0.0817
0.4608 19.0 3477 0.2397 0.0817
0.4583 20.0 3660 0.2397 0.0815
0.4579 21.0 3843 0.2402 0.0817
0.447 22.0 4026 0.2379 0.0813
0.4442 23.0 4209 0.2373 0.0809
0.439 24.0 4392 0.2373 0.0809
0.4381 25.0 4575 0.2376 0.0809
0.4386 26.0 4758 0.2377 0.0807
0.423 27.0 4941 0.2360 0.0804
0.428 28.0 5124 0.2366 0.0803
0.425 29.0 5307 0.2368 0.0804
0.4169 30.0 5490 0.2376 0.0803
0.4253 31.0 5673 0.2367 0.0802
0.4173 32.0 5856 0.2371 0.0802
0.414 33.0 6039 0.2362 0.0800
0.414 34.0 6222 0.2367 0.0803
0.4064 35.0 6405 0.2373 0.0801
0.402 36.0 6588 0.2370 0.0802
0.4035 37.0 6771 0.2369 0.0801

Framework versions

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