metadata

license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - generated_from_trainer
datasets:
  - common_voice_17_0
metrics:
  - wer
  - bleu
model-index:
  - name: wav2vec2-mms-1b-malayalam-colab-CV17.0-v2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_17_0
          type: common_voice_17_0
          config: ml
          split: test
          args: ml
        metrics:
          - name: Wer
            type: wer
            value: 0.5283687943262412
          - name: Bleu
            type: bleu
            value: 0.1996948603256558

wav2vec2-mms-1b-malayalam-colab-CV17.0-v2

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

Loss: 0.2965
Wer: 0.5284
Cer: 0.0934
Bleu: 0.1997

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: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.15
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer	Bleu
5.5563	3.1496	200	0.3157	0.5580	0.1055	0.1800
0.3888	6.2992	400	0.2983	0.5471	0.1003	0.1906
0.3328	9.4488	600	0.3008	0.5542	0.1002	0.1634
0.3006	12.5984	800	0.2821	0.5368	0.0984	0.1888
0.2743	15.7480	1000	0.2913	0.5329	0.0968	0.1813
0.2461	18.8976	1200	0.2822	0.5319	0.0957	0.1937
0.2346	22.0472	1400	0.2933	0.5335	0.0942	0.1848
0.2112	25.1969	1600	0.2885	0.5300	0.0947	0.1900
0.2006	28.3465	1800	0.2944	0.5329	0.0939	0.1870
0.1879	31.4961	2000	0.2965	0.5284	0.0934	0.1997

Framework versions

Transformers 4.42.4
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1