metadata

language:
  - hu
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - hu
  - robust-speech-event
  - model_for_talk
datasets:
  - mozilla-foundation/common_voice_7_0
model-index:
  - name: Akashpb13/xlsr_hungarian_new
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: hu
        metrics:
          - name: Test WER
            type: wer
            value: 0.02698525418772714
          - name: Test CER
            type: cer
            value: 0.005033063261641211
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Dev Data
          type: speech-recognition-community-v2/dev_data
          args: hu
        metrics:
          - name: Test WER
            type: wer
            value: 0.02698525418772714
          - name: Test CER
            type: cer
            value: 0.005033063261641211

Akashpb13/xlsr_hungarian_new

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset. It achieves the following results on evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other, dev and validated datasets):

Loss: 0.184265
Wer: 0.292771

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: 0.000095637994662983496 train_batch_size: 16 eval_batch_size: 16 seed: 13 gradient_accumulation_steps: 16 total_train_batch_size: 316 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: cosine_with_restarts lr_scheduler_warmup_steps: 500 num_epochs: 100 mixed_precision_training: Native AMP

Training results

Step Training Loss Validation Loss Wer 500 4.825900 1.001413 0.810308 1000 0.561400 0.202275 0.361987 1500 0.298900 0.169643 0.326449 2000 0.236500 0.168602 0.316215 2500 0.199100 0.182484 0.308587 3000 0.179100 0.178076 0.303005 3500 0.161500 0.179107 0.299935 4000 0.151700 0.183371 0.295283 4500 0.143700 0.184443 0.295283 5000 0.138900 0.184265 0.292771

Framework versions

Transformers 4.16.0.dev0
Pytorch 1.10.0+cu102
Datasets 1.17.1.dev0
Tokenizers 0.10.3

Evaluation Commands

To evaluate on mozilla-foundation/common_voice_7_0 with split test

python eval.py --model_id Akashpb13/xlsr_hungarian_new --dataset mozilla-foundation/common_voice_7_0 --config hu --split test