readme: ---
  language:
  - es
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-common_voice-es-demo
    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-common_voice-es-demo
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - ES dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1788
  - Wer: 1.0239
  
  ## 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: 15.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | No log        | 0.02  | 100   | 6.6465          | 1.0    |
  | No log        | 0.04  | 200   | 3.0150          | 1.0    |
  | No log        | 0.05  | 300   | 2.8622          | 1.0003 |
  | No log        | 0.07  | 400   | 0.9506          | 0.9771 |
  | 5.1598        | 0.09  | 500   | 0.4883          | 1.0009 |
  | 5.1598        | 0.11  | 600   | 0.3893          | 1.0203 |
  | 5.1598        | 0.13  | 700   | 0.3417          | 1.0283 |
  | 5.1598        | 0.14  | 800   | 0.3352          | 1.0335 |
  | 5.1598        | 0.16  | 900   | 0.2987          | 1.0168 |
  | 0.3671        | 0.18  | 1000  | 0.2921          | 1.0159 |
  | 0.3671        | 0.2   | 1100  | 0.2770          | 1.0096 |
  | 0.3671        | 0.22  | 1200  | 0.2790          | 1.0398 |
  | 0.3671        | 0.24  | 1300  | 0.2659          | 1.0190 |
  | 0.3671        | 0.25  | 1400  | 0.2657          | 1.0528 |
  | 0.289         | 0.27  | 1500  | 0.2556          | 1.0301 |
  | 0.289         | 0.29  | 1600  | 0.2514          | 1.0193 |
  | 0.289         | 0.31  | 1700  | 0.2708          | 1.0699 |
  | 0.289         | 0.33  | 1800  | 0.2455          | 1.0723 |
  | 0.289         | 0.34  | 1900  | 0.2456          | 1.0100 |
  | 0.271         | 0.36  | 2000  | 0.2338          | 1.0533 |
  | 0.271         | 0.38  | 2100  | 0.2479          | 1.0128 |
  | 0.271         | 0.4   | 2200  | 0.2483          | 1.0386 |
  | 0.271         | 0.42  | 2300  | 0.2436          | 1.0528 |
  | 0.271         | 0.43  | 2400  | 0.2382          | 1.0476 |
  | 0.2634        | 0.45  | 2500  | 0.2329          | 1.0680 |
  | 0.2634        | 0.47  | 2600  | 0.2433          | 1.0581 |
  | 0.2634        | 0.49  | 2700  | 0.2354          | 1.0641 |
  | 0.2634        | 0.51  | 2800  | 0.2318          | 1.0504 |
  | 0.2634        | 0.52  | 2900  | 0.2325          | 1.0500 |
  | 0.2522        | 0.54  | 3000  | 0.2344          | 1.0380 |
  | 0.2522        | 0.56  | 3100  | 0.2244          | 1.0663 |
  | 0.2522        | 0.58  | 3200  | 0.2340          | 1.0647 |
  | 0.2522        | 0.6   | 3300  | 0.2288          | 1.0538 |
  | 0.2522        | 0.61  | 3400  | 0.2212          | 1.0614 |
  | 0.2468        | 0.63  | 3500  | 0.2487          | 1.0557 |
  | 0.2468        | 0.65  | 3600  | 0.2330          | 1.0510 |
  | 0.2468        | 0.67  | 3700  | 0.2308          | 1.0506 |
  | 0.2468        | 0.69  | 3800  | 0.2320          | 1.0451 |
  | 0.2468        | 0.71  | 3900  | 0.2261          | 1.0701 |
  | 0.2505        | 0.72  | 4000  | 0.2281          | 1.0713 |
  | 0.2505        | 0.74  | 4100  | 0.2277          | 1.0741 |
  | 0.2505        | 0.76  | 4200  | 0.2253          | 1.0814 |
  | 0.2505        | 0.78  | 4300  | 0.2215          | 1.0437 |
  | 0.2505        | 0.8   | 4400  | 0.2220          | 1.0557 |
  | 0.2434        | 0.81  | 4500  | 0.2184          | 1.0533 |
  | 0.2434        | 0.83  | 4600  | 0.2222          | 1.0819 |
  | 0.2434        | 0.85  | 4700  | 0.2162          | 1.0238 |
  | 0.2434        | 0.87  | 4800  | 0.2132          | 1.0457 |
  | 0.2434        | 0.89  | 4900  | 0.2068          | 1.0611 |
  | 0.2347        | 0.9   | 5000  | 0.2166          | 1.0332 |
  | 0.2347        | 0.92  | 5100  | 0.2087          | 1.0433 |
  | 0.2347        | 0.94  | 5200  | 0.2100          | 1.0292 |
  | 0.2347        | 0.96  | 5300  | 0.2067          | 1.0734 |
  | 0.2347        | 0.98  | 5400  | 0.2148          | 1.0279 |
  | 0.2333        | 0.99  | 5500  | 0.2125          | 1.0277 |
  | 0.2333        | 1.01  | 5600  | 0.2054          | 1.0453 |
  | 0.2333        | 1.03  | 5700  | 0.2091          | 1.0557 |
  | 0.2333        | 1.05  | 5800  | 0.2086          | 1.0239 |
  | 0.2333        | 1.07  | 5900  | 0.2051     