---
license: apache-2.0
tags:
- automatic-speech-recognition
- timit_asr
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: sew-d-small-100k-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. -->

# sew-d-small-100k-timit

This model is a fine-tuned version of [asapp/sew-d-small-100k](https://huggingface.co/asapp/sew-d-small-100k) on the TIMIT_ASR - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7561
- Wer: 0.7971

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.2068        | 0.69  | 100  | 4.0802          | 1.0    |
| 2.9806        | 1.38  | 200  | 2.9792          | 1.0    |
| 2.9781        | 2.07  | 300  | 2.9408          | 1.0    |
| 2.9655        | 2.76  | 400  | 2.9143          | 1.0    |
| 2.8953        | 3.45  | 500  | 2.8774          | 1.0    |
| 2.7712        | 4.14  | 600  | 2.7769          | 0.9999 |
| 2.6662        | 4.83  | 700  | 2.6425          | 0.9789 |
| 2.632         | 5.52  | 800  | 2.5142          | 1.0318 |
| 2.3794        | 6.21  | 900  | 2.4360          | 1.1475 |
| 2.1406        | 6.9   | 1000 | 2.2932          | 0.9962 |
| 2.223         | 7.59  | 1100 | 2.1590          | 0.9281 |
| 2.3607        | 8.28  | 1200 | 2.0553          | 0.8682 |
| 2.1058        | 8.97  | 1300 | 2.0443          | 0.8902 |
| 1.8191        | 9.66  | 1400 | 1.9586          | 0.8237 |
| 1.7013        | 10.34 | 1500 | 1.9586          | 0.8689 |
| 2.2289        | 11.03 | 1600 | 1.9082          | 0.8611 |
| 1.9125        | 11.72 | 1700 | 1.8772          | 0.8150 |
| 1.6424        | 12.41 | 1800 | 1.8671          | 0.7871 |
| 1.6553        | 13.1  | 1900 | 1.8192          | 0.8121 |
| 2.0382        | 13.79 | 2000 | 1.8146          | 0.8440 |
| 1.8785        | 14.48 | 2100 | 1.8094          | 0.8202 |
| 1.6148        | 15.17 | 2200 | 1.8131          | 0.8234 |
| 1.4948        | 15.86 | 2300 | 1.7969          | 0.8256 |
| 1.8844        | 16.55 | 2400 | 1.7790          | 0.8067 |
| 1.8099        | 17.24 | 2500 | 1.7783          | 0.8073 |
| 1.5488        | 17.93 | 2600 | 1.7668          | 0.7971 |
| 1.458         | 18.62 | 2700 | 1.7623          | 0.7973 |
| 1.7656        | 19.31 | 2800 | 1.7574          | 0.8013 |
| 1.7583        | 20.0  | 2900 | 1.7561          | 0.7971 |


### Framework versions

- Transformers 4.12.0.dev0
- Pytorch 1.8.1
- Datasets 1.14.1.dev0
- Tokenizers 0.10.3