metadata

language:
  - hsb
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - hsb
  - robust-speech-event
  - model_for_talk
datasets:
  - common_voice
model-index:
  - name: wav2vec2-large-xls-r-300m-hsb-v1
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 8
          type: mozilla-foundation/common_voice_8_0
          args: tt
        metrics:
          - name: Test WER
            type: wer
            value: null
          - name: Test CER
            type: cer
            value: null

wav2vec2-large-xls-r-300m-hsb-v1

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HSB dataset. It achieves the following results on the evaluation set:

Loss: 0.5684
Wer: 0.4402

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: 0.00045
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: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
8.972	3.23	100	3.7498	1.0
3.3401	6.45	200	3.2320	1.0
3.2046	9.68	300	3.1741	0.9806
2.4031	12.9	400	1.0579	0.8996
1.0427	16.13	500	0.7989	0.7557
0.741	19.35	600	0.6405	0.6299
0.5699	22.58	700	0.6129	0.5928
0.4607	25.81	800	0.6548	0.5695
0.3827	29.03	900	0.6268	0.5190
0.3282	32.26	1000	0.5919	0.5016
0.2764	35.48	1100	0.5953	0.4805
0.2335	38.71	1200	0.5717	0.4728
0.2106	41.94	1300	0.5674	0.4569
0.1859	45.16	1400	0.5685	0.4502
0.1592	48.39	1500	0.5684	0.4402

Framework versions

Transformers 4.16.1
Pytorch 1.10.0+cu111
Datasets 1.18.2
Tokenizers 0.11.0