metadata

library_name: transformers
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-CV17.0
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_17_0
          type: common_voice_17_0
          config: yo
          split: test
          args: yo
        metrics:
          - name: Wer
            type: wer
            value: 0.6538388264431321
          - name: Bleu
            type: bleu
            value: 0.14202013774436864

wav2vec2-mms-1b-CV17.0

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: 0.6919
Wer: 0.6538
Cer: 0.2510
Bleu: 0.1420

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
6.2938	3.0769	200	3.8350	0.9981	0.9092	0.0
2.0522	6.1538	400	0.7219	0.6997	0.2730	0.1116
0.7043	9.2308	600	0.7137	0.7419	0.2682	0.0933
0.6497	12.3077	800	0.6962	0.6664	0.2667	0.1318
0.614	15.3846	1000	0.6680	0.6586	0.2596	0.1356
0.5794	18.4615	1200	0.6798	0.6722	0.2599	0.1254
0.5439	21.5385	1400	0.6724	0.6665	0.2541	0.1287
0.5146	24.6154	1600	0.6906	0.6704	0.2513	0.1327
0.489	27.6923	1800	0.6886	0.6599	0.2509	0.1390
0.4668	30.7692	2000	0.6919	0.6538	0.2510	0.1420

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1