---
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
should probably proofread and complete it, then remove this comment. -->

# 

This model was trained from scratch on the librispeech_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6977
- Wer: 0.1231

## 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: 1000
- num_epochs: 25.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.1467        | 1.68  | 1500  | 6.0558          | 1.3243 |
| 5.4388        | 3.36  | 3000  | 5.4711          | 1.5604 |
| 3.3434        | 5.04  | 4500  | 3.4808          | 0.7461 |
| 1.5259        | 6.73  | 6000  | 2.1931          | 0.3430 |
| 1.4285        | 8.41  | 7500  | 1.5883          | 0.2784 |
| 1.0687        | 10.09 | 9000  | 1.2481          | 0.2069 |
| 0.6425        | 11.77 | 10500 | 1.0507          | 0.1758 |
| 0.7147        | 13.45 | 12000 | 0.9397          | 0.1584 |
| 0.5083        | 15.13 | 13500 | 0.8452          | 0.1453 |
| 0.4287        | 16.82 | 15000 | 0.7915          | 0.1388 |
| 0.3499        | 18.5  | 16500 | 0.7477          | 0.1315 |
| 0.3733        | 20.18 | 18000 | 0.7307          | 0.1287 |
| 0.2609        | 21.86 | 19500 | 0.7061          | 0.1263 |
| 0.2602        | 23.54 | 21000 | 0.6977          | 0.1231 |


### Framework versions

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