mms-1b-bem-genbed-all

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

  • Loss: 0.2479
  • Wer: 0.4062

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: 500
  • num_epochs: 5.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.2747 200 0.6312 0.6736
No log 0.5495 400 0.3199 0.4919
2.9901 0.8242 600 0.3014 0.4613
2.9901 1.0989 800 0.2825 0.4433
0.3968 1.3736 1000 0.2783 0.4541
0.3968 1.6484 1200 0.2732 0.4294
0.3968 1.9231 1400 0.2649 0.4244
0.3766 2.1978 1600 0.2621 0.4204
0.3766 2.4725 1800 0.2628 0.4171
0.3537 2.7473 2000 0.2579 0.4187
0.3537 3.0220 2200 0.2557 0.4034
0.3537 3.2967 2400 0.2524 0.4091
0.3529 3.5714 2600 0.2535 0.4061
0.3529 3.8462 2800 0.2495 0.4034
0.3393 4.1209 3000 0.2494 0.4065
0.3393 4.3956 3200 0.2488 0.4066
0.3393 4.6703 3400 0.2482 0.4028
0.3332 4.9451 3600 0.2479 0.4062

Framework versions

  • Transformers 4.45.0.dev0
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
Downloads last month
11
Safetensors
Model size
965M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for csikasote/mms-1b-bem-genbed-all

Finetuned
(150)
this model