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mms-MGB2

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
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mms-MGB2 / 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-MGB2
    results: []

mms-MGB2

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: nan
  • Wer: 1.0

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
  • training_steps: 10000

Training results

Training Loss Epoch Step Validation Loss Wer
6.8035 0.01 250 5.9077 1.0036
2.2196 0.02 500 2.0224 0.9764
1.0641 0.03 750 0.8949 0.4840
0.8089 0.04 1000 0.7188 0.4095
1.7071 0.05 1250 0.7008 0.3974
0.8132 0.06 1500 0.6975 0.3986
0.9741 0.07 1750 0.6975 0.3986
0.8332 0.08 2000 0.6975 0.3986
0.8908 0.09 2250 0.6975 0.3986
0.8321 0.1 2500 0.6975 0.3986
0.7957 0.1 2750 0.6975 0.3986
0.9173 0.11 3000 0.6975 0.3986
2.0065 0.12 3250 0.6975 0.3986
0.8618 0.13 3500 0.6975 0.3986
0.9001 0.14 3750 0.6975 0.3986
1.0321 0.15 4000 0.6975 0.3986
0.8408 0.16 4250 0.6975 0.3986
0.8901 0.17 4500 0.6975 0.3986
0.8242 0.18 4750 0.6975 0.3986
0.8678 0.19 5000 0.6975 0.3986
0.8633 0.2 5250 0.6975 0.3986
0.8087 0.21 5500 0.6975 0.3986
0.9243 0.22 5750 0.6975 0.3986
0.7973 0.23 6000 0.6975 0.3986
0.835 0.24 6250 0.6975 0.3986
1.3251 0.25 6500 0.6975 0.3986
0.0 0.26 6750 nan 1.0
0.0 0.27 7000 nan 1.0
0.0 0.28 7250 nan 1.0
0.0 0.29 7500 nan 1.0
0.0 0.29 7750 nan 1.0
0.0 0.3 8000 nan 1.0
0.0 0.31 8250 nan 1.0
0.0 0.32 8500 nan 1.0
0.0 0.33 8750 nan 1.0
0.0 0.34 9000 nan 1.0
0.0 0.35 9250 nan 1.0
0.0 0.36 9500 nan 1.0
0.0 0.37 9750 nan 1.0
0.0 0.38 10000 nan 1.0

Framework versions

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