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metadata
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: mascir_fr_hubert_version1000
    results: []

mascir_fr_hubert_version1000

This model is a fine-tuned version of facebook/hubert-large-ls960-ft on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0469
  • Wer: 0.5322

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Wer
No log 2.0 250 3.0909 1.0
5.0589 4.0 500 2.9060 1.0
5.0589 6.0 750 1.3938 0.9789
1.8801 8.0 1000 0.9636 0.8422
1.8801 10.0 1250 0.8361 0.7644
0.8006 12.0 1500 0.8474 0.7444
0.8006 14.0 1750 0.8360 0.7078
0.5307 16.0 2000 0.8514 0.6944
0.5307 18.0 2250 0.8770 0.6544
0.3998 20.0 2500 0.8200 0.65
0.3998 22.0 2750 0.8362 0.63
0.3281 24.0 3000 0.8933 0.6144
0.3281 26.0 3250 0.9355 0.62
0.262 28.0 3500 0.9134 0.6222
0.262 30.0 3750 0.9302 0.5989
0.2256 32.0 4000 0.9307 0.5856
0.2256 34.0 4250 0.9078 0.6011
0.2011 36.0 4500 0.9647 0.5822
0.2011 38.0 4750 0.9252 0.5844
0.1819 40.0 5000 0.9917 0.5711
0.1819 42.0 5250 0.9577 0.5678
0.1706 44.0 5500 1.0094 0.5722
0.1706 46.0 5750 0.9774 0.5722
0.1504 48.0 6000 0.9702 0.5456
0.1504 50.0 6250 0.9575 0.5756
0.1509 52.0 6500 0.9855 0.5644
0.1509 54.0 6750 0.9429 0.5411
0.1292 56.0 7000 1.0471 0.5644
0.1292 58.0 7250 1.0106 0.5589
0.1217 60.0 7500 1.0118 0.5544
0.1217 62.0 7750 1.0415 0.5478
0.1187 64.0 8000 1.0047 0.5489
0.1187 66.0 8250 1.0700 0.5644
0.1075 68.0 8500 1.0357 0.5444
0.1075 70.0 8750 0.9647 0.5444
0.1009 72.0 9000 1.0392 0.5489
0.1009 74.0 9250 1.0569 0.5433
0.0997 76.0 9500 1.0266 0.5456
0.0997 78.0 9750 1.0328 0.54
0.101 80.0 10000 1.0338 0.5522
0.101 82.0 10250 1.0422 0.5511
0.088 84.0 10500 1.0233 0.55
0.088 86.0 10750 1.0446 0.5522
0.0922 88.0 11000 1.0558 0.5467
0.0922 90.0 11250 1.0405 0.5433
0.0863 92.0 11500 1.0336 0.5322
0.0863 94.0 11750 1.0575 0.5356
0.0845 96.0 12000 1.0449 0.5378
0.0845 98.0 12250 1.0482 0.5344
0.0818 100.0 12500 1.0469 0.5322

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.3
  • Tokenizers 0.13.3