metadata

tags:
  - generated_from_trainer
datasets:
  - evanarlian/common_voice_11_0_id_filtered
metrics:
  - wer
model-index:
  - name: wav2vec2-xls-r-164m-id
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: evanarlian/common_voice_11_0_id_filtered
          type: evanarlian/common_voice_11_0_id_filtered
        metrics:
          - name: Wer
            type: wer
            value: 0.2923162069919749

wav2vec2-xls-r-164m-id

This model is a fine-tuned version of evanarlian/distil-wav2vec2-xls-r-164m-id on the evanarlian/common_voice_11_0_id_filtered dataset. It achieves the following results on the evaluation set:

Loss: 0.2865
Wer: 0.2923

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: 0.0001
train_batch_size: 24
eval_batch_size: 24
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.3
num_epochs: 80.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.4047	4.59	5000	1.0167	0.9138
0.587	9.18	10000	0.4639	0.5615
0.3782	13.77	15000	0.3375	0.4496
0.2867	18.37	20000	0.2881	0.4022
0.2519	22.96	25000	0.2775	0.3700
0.1941	27.55	30000	0.2701	0.3516
0.1727	32.14	35000	0.2795	0.3486
0.1448	36.73	40000	0.2878	0.3364
0.1251	41.32	45000	0.2649	0.3275
0.113	45.91	50000	0.2862	0.3168
0.0994	50.51	55000	0.2798	0.3091
0.0938	55.1	60000	0.2864	0.3070
0.0853	59.69	65000	0.2860	0.3069
0.0724	64.28	70000	0.2994	0.3003
0.0723	68.87	75000	0.2951	0.2983
0.0666	73.46	80000	0.2886	0.2941
0.0659	78.05	85000	0.2865	0.2923

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.9.1.dev0
Tokenizers 0.13.2