mms-MGB3 / README.md
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metadata
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: mms-MGB3
    results: []

mms-MGB3

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:

  • Loss: 3.5770
  • Wer: 99.9986

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: 1e-05
  • train_batch_size: 14
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Wer
8.1649 0.83 250 8.8182 100.0211
4.4764 1.66 500 5.1784 100.0254
3.962 2.48 750 4.6853 100.0310
3.7546 3.31 1000 4.4820 101.1220
3.5712 4.14 1250 4.3419 101.5181
5.9242 4.97 1500 4.2276 100.0
6.072 5.79 1750 4.1441 100.0
3.3164 6.62 2000 4.0701 100.0
3.2964 7.45 2250 3.9941 100.0
3.2501 8.28 2500 3.9978 100.0
3.2477 9.11 2750 3.9468 100.0
3.9197 9.93 3000 3.9109 100.0
3.1928 10.76 3250 3.8802 100.0
3.182 11.59 3500 3.8802 100.0
3.181 12.42 3750 3.7959 100.0
4.3975 13.25 4000 3.8292 100.0
3.8885 14.07 4250 3.7765 100.0
4.2643 14.9 4500 3.7765 100.0
3.1381 15.73 4750 3.7338 100.0
3.1197 16.56 5000 3.7391 100.0
3.1345 17.38 5250 3.7267 100.0
4.4275 18.21 5500 3.7405 100.0
4.3669 19.04 5750 3.7220 100.0
3.1225 19.87 6000 3.7093 99.9915
3.8043 20.7 6250 3.6449 99.9958
3.8089 21.52 6500 3.6988 100.0
4.2457 22.35 6750 3.6125 100.0
3.0956 23.18 7000 3.6309 99.9972
3.1013 24.01 7250 3.5845 99.9930
5.8493 24.83 7500 3.5770 99.9986

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1
  • Datasets 2.19.1
  • Tokenizers 0.13.3