readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-0.25-Temp-1-mse
    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. -->
  
  # libri-alpha-0.25-Temp-1-mse
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 16.7446
  - Wer: 0.1212
  
  ## 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: 2e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 122.8866      | 0.75  | 100  | 35.8349         | 0.1501 |
  | 96.5187       | 1.49  | 200  | 31.6506         | 0.1453 |
  | 88.8912       | 2.24  | 300  | 23.5288         | 0.1459 |
  | 82.3478       | 2.99  | 400  | 20.1852         | 0.1386 |
  | 74.9987       | 3.73  | 500  | 19.2132         | 0.1327 |
  | 71.3929       | 4.48  | 600  | 18.6715         | 0.1320 |
  | 67.5429       | 5.22  | 700  | 18.1638         | 0.1275 |
  | 65.8387       | 5.97  | 800  | 17.9401         | 0.1274 |
  | 62.2889       | 6.72  | 900  | 17.5666         | 0.1254 |
  | 62.4649       | 7.46  | 1000 | 17.5202         | 0.1251 |
  | 61.3213       | 8.21  | 1100 | 17.1763         | 0.1250 |
  | 59.1153       | 8.96  | 1200 | 17.2310         | 0.1229 |
  | 61.095        | 9.7   | 1300 | 17.0079         | 0.1228 |
  | 61.0961       | 10.45 | 1400 | 16.8989         | 0.1214 |
  | 59.0814       | 11.19 | 1500 | 16.9785         | 0.1195 |
  | 58.3763       | 11.94 | 1600 | 17.0034         | 0.1198 |
  | 57.9529       | 12.69 | 1700 | 16.8352         | 0.1203 |
  | 56.6213       | 13.43 | 1800 | 16.8661         | 0.1206 |
  | 56.4495       | 14.18 | 1900 | 16.8180         | 0.1216 |
  | 54.3606       | 14.93 | 2000 | 16.7446         | 0.1212 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  