readme: ---
  language:
  - fi
  license: apache-2.0
  tags:
  - generated_from_trainer
  - automatic-speech-recognition
  - robust-speech-event
  - hf-asr-leaderboard
  model-index:
  - name: wav2vec2-xlsr-fi-lm-1B
    results: []
  ---
  
  <!-- 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. -->
  
  # wav2vec2-xlsr-fi-lm-1B
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common voice train/dev/other datasets.
  It achieves the following results on the evaluation set without language model:
  - Loss: 0.1853
  - Wer: 0.2205
  
  With language model:
  - Wer: 0.1026
  
  
  ## 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: 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: 500
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.8158        | 0.67  | 400  | 0.4835          | 0.6310 |
  | 0.5679        | 1.33  | 800  | 0.4806          | 0.5538 |
  | 0.6055        | 2.0   | 1200 | 0.3888          | 0.5083 |
  | 0.5353        | 2.67  | 1600 | 0.3258          | 0.4365 |
  | 0.4883        | 3.33  | 2000 | 0.3313          | 0.4204 |
  | 0.4513        | 4.0   | 2400 | 0.2924          | 0.3904 |
  | 0.3753        | 4.67  | 2800 | 0.2593          | 0.3608 |
  | 0.3478        | 5.33  | 3200 | 0.2832          | 0.3551 |
  | 0.3796        | 6.0   | 3600 | 0.2495          | 0.3402 |
  | 0.2556        | 6.67  | 4000 | 0.2342          | 0.3106 |
  | 0.229         | 7.33  | 4400 | 0.2181          | 0.2812 |
  | 0.205         | 8.0   | 4800 | 0.2041          | 0.2523 |
  | 0.1654        | 8.67  | 5200 | 0.2015          | 0.2416 |
  | 0.152         | 9.33  | 5600 | 0.1942          | 0.2294 |
  | 0.1569        | 10.0  | 6000 | 0.1853          | 0.2205 |
  
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - Pytorch 1.10.1+cu102
  - Datasets 1.17.1.dev0
  - Tokenizers 0.11.0
  