readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-0.5-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-0.5-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: 28.9681
  - Wer: 0.1160
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 212.5522      | 0.75  | 100  | 55.9161         | 0.1500 |
  | 171.0676      | 1.49  | 200  | 51.5701         | 0.1434 |
  | 159.3247      | 2.24  | 300  | 40.6680         | 0.1416 |
  | 147.7202      | 2.99  | 400  | 36.0320         | 0.1388 |
  | 136.0871      | 3.73  | 500  | 32.8709         | 0.1323 |
  | 126.3071      | 4.48  | 600  | 31.9204         | 0.1298 |
  | 126.9502      | 5.22  | 700  | 31.0903         | 0.1281 |
  | 117.0498      | 5.97  | 800  | 30.5398         | 0.1272 |
  | 117.0928      | 6.72  | 900  | 30.2616         | 0.1262 |
  | 116.35        | 7.46  | 1000 | 30.2445         | 0.1264 |
  | 116.784       | 8.21  | 1100 | 30.0181         | 0.1268 |
  | 111.6779      | 8.96  | 1200 | 29.6434         | 0.1252 |
  | 110.2514      | 9.7   | 1300 | 29.6900         | 0.1233 |
  | 112.603       | 10.45 | 1400 | 29.4023         | 0.1240 |
  | 110.4294      | 11.19 | 1500 | 29.5929         | 0.1239 |
  | 106.3693      | 11.94 | 1600 | 29.4228         | 0.1232 |
  | 102.5095      | 12.69 | 1700 | 29.6106         | 0.1236 |
  | 104.8351      | 13.43 | 1800 | 29.3908         | 0.1220 |
  | 103.6225      | 14.18 | 1900 | 29.5250         | 0.1216 |
  | 102.5769      | 14.93 | 2000 | 29.4744         | 0.1211 |
  | 102.7153      | 15.67 | 2100 | 29.3769         | 0.1203 |
  | 98.3215       | 16.42 | 2200 | 29.3692         | 0.1205 |
  | 100.0971      | 17.16 | 2300 | 29.0029         | 0.1183 |
  | 94.876        | 17.91 | 2400 | 28.9354         | 0.1181 |
  | 100.2511      | 18.66 | 2500 | 28.9513         | 0.1168 |
  | 95.3128       | 19.4  | 2600 | 29.0832         | 0.1166 |
  | 95.2151       | 20.15 | 2700 | 29.0161         | 0.1157 |
  | 92.6844       | 20.9  | 2800 | 29.0543         | 0.1152 |
  | 96.837        | 21.64 | 2900 | 29.2276         | 0.1164 |
  | 94.2866       | 22.39 | 3000 | 28.9697         | 0.1164 |
  | 92.1945       | 23.13 | 3100 | 29.0823         | 0.1169 |
  | 97.7153       | 23.88 | 3200 | 29.0628         | 0.1158 |
  | 95.3836       | 24.63 | 3300 | 28.9681         | 0.1160 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  