readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - ascend
  model-index:
  - name: wav2vec2-large-xlsr-ascend
    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-large-xlsr-ascend
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ascend dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.9059
  - Wer: 0.6633
  
  ## 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 22.8456       | 1.32  | 400  | 5.4265          | 1.0    |
  | 5.1649        | 2.65  | 800  | 5.0265          | 1.0    |
  | 4.8311        | 3.97  | 1200 | 4.7929          | 1.0    |
  | 4.5407        | 5.3   | 1600 | 4.5517          | 1.0    |
  | 4.0548        | 6.62  | 2000 | 3.9723          | 0.9219 |
  | 3.2573        | 7.95  | 2400 | 3.2263          | 0.7997 |
  | 2.4774        | 9.27  | 2800 | 2.9549          | 0.7244 |
  | 1.9606        | 10.6  | 3200 | 2.8674          | 0.7015 |
  | 1.5414        | 11.92 | 3600 | 3.0565          | 0.6604 |
  | 1.1045        | 13.24 | 4000 | 3.0344          | 0.6614 |
  | 0.7768        | 14.57 | 4400 | 3.0164          | 0.6811 |
  | 0.5191        | 15.89 | 4800 | 3.2068          | 0.6432 |
  | 0.3           | 17.22 | 5200 | 3.4341          | 0.6638 |
  | 0.1713        | 18.54 | 5600 | 3.7193          | 0.6611 |
  | 0.0987        | 19.87 | 6000 | 4.0413          | 0.6570 |
  | 0.05          | 21.19 | 6400 | 4.5981          | 0.6769 |
  | 0.0321        | 22.52 | 6800 | 4.6013          | 0.6766 |
  | 0.0198        | 23.84 | 7200 | 4.3965          | 0.6714 |
  | 0.0091        | 25.17 | 7600 | 4.6236          | 0.6621 |
  | 0.006         | 26.49 | 8000 | 4.7604          | 0.6606 |
  | 0.0044        | 27.81 | 8400 | 4.8233          | 0.6612 |
  | 0.0027        | 29.14 | 8800 | 4.9059          | 0.6633 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.13.1
  