readme: ---
  language:
  - sv-SE
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - hello
  - model_for_talk
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
  - sv
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: XLS-R-300M - Swedish
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: sv-SE
      metrics:
      - name: Test WER
        type: wer
        value: 16.98
      - name: Test CER
        type: cer
        value: 5.66
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: sv
      metrics:
      - name: Test WER
        type: wer
        value: 27.01
      - name: Test CER
        type: cer
        value: 13.14
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # XLS-R-300m-SV
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - SV-SE dataset.
  It achieves the following results on the evaluation set:
  
  - Loss: 0.3171
  - Wer: 0.2468
  
  ## 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: 7.5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - 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: 2000
  - num_epochs: 50.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 3.3349        | 1.45  | 500   | 3.2858          | 1.0    |
  | 2.9298        | 2.91  | 1000  | 2.9225          | 1.0000 |
  | 2.0839        | 4.36  | 1500  | 1.1546          | 0.8295 |
  | 1.7093        | 5.81  | 2000  | 0.6827          | 0.5701 |
  | 1.5855        | 7.27  | 2500  | 0.5597          | 0.4947 |
  | 1.4831        | 8.72  | 3000  | 0.4923          | 0.4527 |
  | 1.4416        | 10.17 | 3500  | 0.4670          | 0.4270 |
  | 1.3848        | 11.63 | 4000  | 0.4341          | 0.3980 |
  | 1.3749        | 13.08 | 4500  | 0.4203          | 0.4011 |
  | 1.3311        | 14.53 | 5000  | 0.4310          | 0.3961 |
  | 1.317         | 15.99 | 5500  | 0.3898          | 0.4322 |
  | 1.2799        | 17.44 | 6000  | 0.3806          | 0.3572 |
  | 1.2771        | 18.89 | 6500  | 0.3828          | 0.3427 |
  | 1.2451        | 20.35 | 7000  | 0.3702          | 0.3359 |
  | 1.2182        | 21.8  | 7500  | 0.3685          | 0.3270 |
  | 1.2152        | 23.26 | 8000  | 0.3650          | 0.3308 |
  | 1.1837        | 24.71 | 8500  | 0.3568          | 0.3187 |
  | 1.1721        | 26.16 | 9000  | 0.3659          | 0.3249 |
  | 1.1764        | 27.61 | 9500  | 0.3547          | 0.3145 |
  | 1.1606        | 29.07 | 10000 | 0.3514          | 0.3104 |
  | 1.1431        | 30.52 | 10500 | 0.3469          | 0.3062 |
  | 1.1047        | 31.97 | 11000 | 0.3313          | 0.2979 |
  | 1.1315        | 33.43 | 11500 | 0.3298          | 0.2992 |
  | 1.1022        | 34.88 | 12000 | 0.3296          | 0.2973 |
  | 1.0935        | 36.34 | 12500 | 0.3278          | 0.2926 |
  | 1.0676        | 37.79 | 13000 | 0.3208          | 0.2868 |
  | 1.0571        | 39.24 | 13500 | 0.3322          | 0.2885 |
  | 1.0536        | 40.7  | 14000 | 0.3245          | 0.2831 |
  | 1.0525        | 42.15 | 14500 | 0.3285          | 0.2826 |
  | 1.0464        | 43.6  | 15000 | 0.3223          | 0.2796 |
  | 1.0415        | 45.06 | 15500 | 0.3166          | 0.2774 |
  | 1.0356        | 46.51 | 16000 | 0.3177          | 0.2746 |
  | 1.04          | 47.96 | 16500 | 0.3150          | 0.2735 |
  | 1.0209        | 49.42 | 17000 | 0.3175          | 0.2731 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.0+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.10.3
  
  #### Evaluation Commands
  
  1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test`
  
  ```bash
  python eval.py --model_id hf-test/xls-r-300m-sv --dataset mozilla-foundation/common_voice_7_0 --config sv-SE --split test
  ```
  
  2. To evaluate on `speech-recognition-community-v2/dev_data`
  
  ```bash
  python eval.py --model_id hf-test/xls-r-300m-sv --dataset speech-recognition-community-v2/dev_data --config sv --split validation --chunk_length_s 5.0 --stride_length_s 1.0
  ```
  
  ### Inference With LM
  
  ```python
  import torch
  from datasets import load_dataset
  from transformers import AutoModelForCTC, Auto