readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-960h-lv60-self-with-wikipedia-lm-timit
    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-960h-lv60-self-with-wikipedia-lm-timit
  
  This model is a fine-tuned version of [gxbag/wav2vec2-large-960h-lv60-self-with-wikipedia-lm](https://huggingface.co/gxbag/wav2vec2-large-960h-lv60-self-with-wikipedia-lm) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0889
  - Wer: 0.4976
  
  ## 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: 1000
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 7.7911        | 2.02  | 250  | 3.0896          | 1.0    |
  | 1.3854        | 4.03  | 500  | 0.0704          | 0.5052 |
  | 0.1926        | 6.05  | 750  | 0.0678          | 0.5010 |
  | 0.1472        | 8.06  | 1000 | 0.0794          | 0.5157 |
  | 0.1326        | 10.08 | 1250 | 0.0937          | 0.5031 |
  | 0.104         | 12.1  | 1500 | 0.0859          | 0.5055 |
  | 0.0754        | 14.11 | 1750 | 0.0903          | 0.5031 |
  | 0.0624        | 16.13 | 2000 | 0.0927          | 0.5034 |
  | 0.0594        | 18.14 | 2250 | 0.0929          | 0.5016 |
  | 0.057         | 20.16 | 2500 | 0.0873          | 0.5039 |
  | 0.0476        | 22.18 | 2750 | 0.0974          | 0.5055 |
  | 0.0382        | 24.19 | 3000 | 0.0886          | 0.5003 |
  | 0.0329        | 26.21 | 3250 | 0.0832          | 0.4987 |
  | 0.032         | 28.22 | 3500 | 0.0889          | 0.4976 |
  
  
  ### Framework versions
  
  - Transformers 4.23.0.dev0
  - Pytorch 1.13.0.dev20220624+cu113
  - Datasets 2.5.2.dev0
  - Tokenizers 0.12.1
  