pytorch tensorboard speech-encoder-decoder automatic-speech-recognition dataset:librispeech_asr transformers generated_from_trainer model-index
---
tags:
- generated_from_trainer
datasets:
- librispeech_asr
model-index:
- name: ''
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 

This model was trained from scratch on the librispeech_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 5.6120
- Wer: 1.0267

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.7189        | 0.56  | 500  | 6.9796          | 0.9350 |
| 6.5068        | 1.12  | 1000 | 6.4823          | 1.3923 |
| 6.4601        | 1.68  | 1500 | 6.1801          | 1.1578 |
| 6.1802        | 2.24  | 2000 | 6.0002          | 1.7750 |
| 6.0888        | 2.8   | 2500 | 5.8453          | 1.7581 |
| 6.0993        | 3.36  | 3000 | 5.7702          | 1.4096 |
| 6.0851        | 3.92  | 3500 | 5.6634          | 1.0944 |
| 5.9357        | 4.48  | 4000 | 5.6120          | 1.0267 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.3
- Tokenizers 0.11.0
