readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: fine_tuned_t5_model
    results:
    - task:
        type: automatic-speech-recognition
      dataset:
        type: librispeech_asr
        name: Librispeech (clean)
        config: other
        split: test
        args:
          language: en
      metrics:
      - type: wer
        value: 8.1
        name: WER
  ---
  
  <!-- 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. -->
  
  # fine_tuned_t5_model
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0736
  - Bleu: 0.0099
  - Gen Len: 19.0
  
  ## 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: 0.002
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
  | No log        | 1.0   | 157  | 1.9566          | 0.0074 | 19.0    |
  | No log        | 2.0   | 314  | 1.8330          | 0.026  | 19.0    |
  | No log        | 3.0   | 471  | 1.7957          | 0.0405 | 19.0    |
  | 1.9115        | 4.0   | 628  | 1.7441          | 0.0073 | 19.0    |
  | 1.9115        | 5.0   | 785  | 1.7875          | 0.033  | 19.0    |
  | 1.9115        | 6.0   | 942  | 2.0419          | 0.0093 | 19.0    |
  | 1.5066        | 7.0   | 1099 | 2.0750          | 0.0099 | 19.0    |
  | 1.5066        | 8.0   | 1256 | 2.0744          | 0.0099 | 19.0    |
  | 1.5066        | 9.0   | 1413 | 2.0738          | 0.0099 | 19.0    |
  | 1.6163        | 10.0  | 1570 | 2.0736          | 0.0099 | 19.0    |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  