metadata

language:
  - sl
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - sl
  - robust-speech-event
  - model_for_talk
  - hf-asr-leaderboard
datasets:
  - mozilla-foundation/common_voice_7_0
model-index:
  - name: XLS-R-300M - Slovenian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: sl
        metrics:
          - name: Test WER
            type: wer
            value: 18.97
          - name: Test CER
            type: cer
            value: 4.534
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Dev Data
          type: speech-recognition-community-v2/dev_data
          args: sl
        metrics:
          - name: Test WER
            type: wer
            value: 55.048
          - name: Test CER
            type: cer
            value: 22.739
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Test Data
          type: speech-recognition-community-v2/eval_data
          args: sl
        metrics:
          - name: Test WER
            type: wer
            value: 54.81

wav2vec2-large-xls-r-300m-slovenian

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - SL dataset. It achieves the following results on the evaluation set:

Loss: 0.2093
Wer: 0.1907

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: 7e-05
train_batch_size: 32
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 100.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.785	12.5	1000	0.7465	0.6812
0.8989	25.0	2000	0.2495	0.2732
0.7118	37.5	3000	0.2126	0.2284
0.6367	50.0	4000	0.2049	0.2049
0.5763	62.5	5000	0.2116	0.2055
0.5196	75.0	6000	0.2111	0.1910
0.4949	87.5	7000	0.2131	0.1931
0.4797	100.0	8000	0.2093	0.1907

Framework versions

Transformers 4.16.0.dev0
Pytorch 1.10.1+cu102
Datasets 1.18.3
Tokenizers 0.11.0