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mms-zeroshot-300m-genbed-combined-model

This model is a fine-tuned version of mms-meta/mms-zeroshot-300m on the GENBED - BEM dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2768
  • Wer: 0.4294

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: 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: 100
  • num_epochs: 30.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.2747 200 2.2031 1.0
No log 0.5495 400 0.4235 0.6042
2.7468 0.8242 600 0.3791 0.5722
2.7468 1.0989 800 0.3588 0.5632
0.5446 1.3736 1000 0.3489 0.5446
0.5446 1.6484 1200 0.3406 0.5458
0.5446 1.9231 1400 0.3326 0.5183
0.4932 2.1978 1600 0.3235 0.5237
0.4932 2.4725 1800 0.3202 0.5058
0.4644 2.7473 2000 0.3204 0.504
0.4644 3.0220 2200 0.3144 0.4910
0.4644 3.2967 2400 0.3076 0.4957
0.4505 3.5714 2600 0.3039 0.4751
0.4505 3.8462 2800 0.3027 0.4785
0.433 4.1209 3000 0.3013 0.4682
0.433 4.3956 3200 0.2961 0.4765
0.433 4.6703 3400 0.2914 0.468
0.4203 4.9451 3600 0.2909 0.4656
0.4203 5.2198 3800 0.2946 0.4508
0.4042 5.4945 4000 0.2901 0.4434
0.4042 5.7692 4200 0.2900 0.4463
0.4042 6.0440 4400 0.2840 0.4449
0.3962 6.3187 4600 0.2820 0.4448
0.3962 6.5934 4800 0.2771 0.4326
0.3881 6.8681 5000 0.2768 0.4294
0.3881 7.1429 5200 0.2787 0.4385
0.3881 7.4176 5400 0.2795 0.4309
0.3784 7.6923 5600 0.2803 0.4357

Framework versions

  • Transformers 4.46.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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