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---
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