metadata

license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
  - generated_from_trainer
datasets:
  - common_voice_16_0
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xls-r-300m-hi-colab
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_16_0
          type: common_voice_16_0
          config: hi
          split: test
          args: hi
        metrics:
          - name: Wer
            type: wer
            value: 0.4948465637275874

wav2vec2-large-xls-r-300m-hi-colab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.6983
Wer: 0.4948

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: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.491	1.8059	400	1.3703	0.9679
0.6981	3.6117	800	0.7041	0.6607
0.3758	5.4176	1200	0.6709	0.6185
0.2736	7.2235	1600	0.7170	0.5925
0.2089	9.0293	2000	0.6445	0.5722
0.1686	10.8352	2400	0.7004	0.5770
0.1408	12.6411	2800	0.7097	0.5735
0.1227	14.4470	3200	0.6763	0.5533
0.1056	16.2528	3600	0.7245	0.5484
0.0923	18.0587	4000	0.7198	0.5480
0.083	19.8646	4400	0.6568	0.5251
0.0742	21.6704	4800	0.7183	0.5252
0.0647	23.4763	5200	0.7306	0.5141
0.0574	25.2822	5600	0.7236	0.5063
0.052	27.0880	6000	0.7234	0.4969
0.0478	28.8939	6400	0.6983	0.4948

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1