readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-1-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-1-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: 53.0700
  - Wer: 0.1137
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 406.6609      | 0.75  | 100  | 92.6621         | 0.1514 |
  | 332.8654      | 1.49  | 200  | 75.1632         | 0.1429 |
  | 300.7975      | 2.24  | 300  | 69.9229         | 0.1413 |
  | 288.1078      | 2.99  | 400  | 66.7404         | 0.1361 |
  | 262.5671      | 3.73  | 500  | 60.1363         | 0.1314 |
  | 246.594       | 4.48  | 600  | 59.8725         | 0.1289 |
  | 232.3433      | 5.22  | 700  | 59.7349         | 0.1274 |
  | 232.5868      | 5.97  | 800  | 58.1594         | 0.1266 |
  | 225.2652      | 6.72  | 900  | 57.0715         | 0.1248 |
  | 222.3506      | 7.46  | 1000 | 56.8740         | 0.1253 |
  | 210.8775      | 8.21  | 1100 | 55.6375         | 0.1235 |
  | 210.2934      | 8.96  | 1200 | 54.7285         | 0.1223 |
  | 212.0601      | 9.7   | 1300 | 54.6263         | 0.1224 |
  | 203.2785      | 10.45 | 1400 | 54.7651         | 0.1241 |
  | 200.5735      | 11.19 | 1500 | 54.7737         | 0.1238 |
  | 199.7971      | 11.94 | 1600 | 54.7460         | 0.1214 |
  | 198.5452      | 12.69 | 1700 | 54.5335         | 0.1222 |
  | 192.6993      | 13.43 | 1800 | 54.3382         | 0.1209 |
  | 195.9604      | 14.18 | 1900 | 54.0138         | 0.1188 |
  | 190.6209      | 14.93 | 2000 | 55.2720         | 0.1219 |
  | 197.205       | 15.67 | 2100 | 54.4430         | 0.1193 |
  | 182.2428      | 16.42 | 2200 | 53.7938         | 0.1195 |
  | 183.4877      | 17.16 | 2300 | 53.0349         | 0.1151 |
  | 178.3634      | 17.91 | 2400 | 53.0706         | 0.1157 |
  | 184.3548      | 18.66 | 2500 | 53.0254         | 0.1158 |
  | 184.6175      | 19.4  | 2600 | 53.2929         | 0.1159 |
  | 190.0462      | 20.15 | 2700 | 52.8959         | 0.1157 |
  | 179.8124      | 20.9  | 2800 | 53.0652         | 0.1147 |
  | 178.4741      | 21.64 | 2900 | 53.5907         | 0.1155 |
  | 175.1646      | 22.39 | 3000 | 53.5027         | 0.1155 |
  | 172.7706      | 23.13 | 3100 | 53.3478         | 0.1146 |
  | 182.5294      | 23.88 | 3200 | 53.2863         | 0.1152 |
  | 183.6617      | 24.63 | 3300 | 53.3587         | 0.1146 |
  | 180.0207      | 25.37 | 3400 | 53.2285         | 0.1140 |
  | 180.7319      | 26.12 | 3500 | 53.1544         | 0.1140 |
  | 171.5148      | 26.87 | 3600 | 53.0734         | 0.1144 |
  | 177.4159      | 27.61 | 3700 | 53.1536         | 0.1138 |
  | 168.6823      | 28.36 | 3800 | 53.1117         | 0.1138 |
  | 176.7611      | 29.1  | 3900 | 53.0962         | 0.1135 |
  | 176.1258      | 29.85 | 4000 | 53.0700         | 0.1137 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  