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mms-1b-bigcgen-male-5hrs-model

Automatic Speech Recognition
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bigcgen
mms
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metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - automatic-speech-recognition
  - bigcgen
  - mms
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: mms-1b-bigcgen-male-5hrs-model
    results: []

mms-1b-bigcgen-male-5hrs-model

This model is a fine-tuned version of facebook/mms-1b-all on the BIGCGEN - BEM dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4408
  • Wer: 0.4520

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: 0.0003
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Use 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: 30.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
12.4451 0.3106 100 1.2035 0.8329
1.6342 0.6211 200 0.6175 0.5759
1.5403 0.9317 300 0.5695 0.5535
1.3778 1.2422 400 0.5524 0.5359
1.4572 1.5528 500 0.5302 0.5172
1.4042 1.8634 600 0.5179 0.5266
1.4053 2.1739 700 0.5029 0.5143
1.2782 2.4845 800 0.4701 0.4864
1.2541 2.7950 900 0.4585 0.4867
1.1672 3.1056 1000 0.4728 0.4862
1.1205 3.4161 1100 0.4558 0.4794
1.1699 3.7267 1200 0.4520 0.4811
1.2418 4.0373 1300 0.4495 0.4751
1.071 4.3478 1400 0.4487 0.4737
1.078 4.6584 1500 0.4446 0.4761
1.2474 4.9689 1600 0.4437 0.4626
1.1127 5.2795 1700 0.4380 0.4657
1.1761 5.5901 1800 0.4480 0.4674
1.0997 5.9006 1900 0.4470 0.4653
1.1203 6.2112 2000 0.4421 0.4614
1.0749 6.5217 2100 0.4344 0.4506
1.1156 6.8323 2200 0.4354 0.4511
1.0404 7.1429 2300 0.4364 0.4535
1.1081 7.4534 2400 0.4377 0.4516
1.0535 7.7640 2500 0.4407 0.4520

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0