metadata

license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - generated_from_trainer
datasets:
  - common_voice_6_1
metrics:
  - wer
model-index:
  - name: wav2vec2-common_voice-ta
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_6_1
          type: common_voice_6_1
          config: ta
          split: test
          args: ta
        metrics:
          - name: Wer
            type: wer
            value: 0.7094281298299846

wav2vec2-common_voice-ta

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_6_1 dataset. It achieves the following results on the evaluation set:

Loss: 0.6599
Wer: 0.7094

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: 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_steps: 500
num_epochs: 15.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.84	100	4.3941	1.0
No log	1.69	200	3.2005	1.0
No log	2.53	300	2.7844	1.0145
No log	3.38	400	0.8691	1.0003
4.317	4.22	500	0.6846	0.8394
4.317	5.06	600	0.6270	0.7790
4.317	5.91	700	0.5935	0.7802
4.317	6.75	800	0.5701	0.7812
4.317	7.59	900	0.5649	0.7891
0.3656	8.44	1000	0.6092	0.8178
0.3656	9.28	1100	0.6093	0.7721
0.3656	10.13	1200	0.6154	0.7287
0.3656	10.97	1300	0.6284	0.7408
0.3656	11.81	1400	0.6343	0.7143
0.1681	12.66	1500	0.6523	0.7363
0.1681	13.5	1600	0.6543	0.7139
0.1681	14.35	1700	0.6599	0.7094

Framework versions

Transformers 4.38.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1