metadata

library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-fl102
tags:
  - generated_from_trainer
datasets:
  - common_voice_17_0
metrics:
  - wer
model-index:
  - name: wav2vec2-large-mms-1b102-ckb_30cent
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_17_0
          type: common_voice_17_0
          config: ckb
          split: test
          args: ckb
        metrics:
          - name: Wer
            type: wer
            value: 0.4114560559685177

wav2vec2-large-mms-1b102-ckb_30cent

This model is a fine-tuned version of facebook/mms-1b-fl102 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.3046
Wer: 0.4115

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: 0.001
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.1601	4.0988	500	0.3159	0.4227
0.5802	8.1975	1000	0.3046	0.4115

Framework versions

Transformers 4.48.0.dev0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0