---
license: apache-2.0
tags:
- automatic-speech-recognition
- librispeech_asr
- generated_from_trainer
model-index:
- name: sew-mid-100k-librispeech-clean-100h-ft
  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-mid-100k-librispeech-clean-100h-ft

This model is a fine-tuned version of [asapp/sew-mid-100k](https://huggingface.co/asapp/sew-mid-100k) on the LIBRISPEECH_ASR - CLEAN dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9609
- Wer: 1.0

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 2.9558        | 0.11  | 100  | 2.9238          | 1.0 |
| 2.8978        | 0.22  | 200  | 2.9614          | 1.0 |
| 2.9267        | 0.34  | 300  | 3.3049          | 1.0 |
| 3.1351        | 0.45  | 400  | 2.9246          | 1.0 |
| 3.4365        | 0.56  | 500  | 4.2798          | 1.0 |
| 3.1861        | 0.67  | 600  | 4.0740          | 1.0 |
| 2.914         | 0.78  | 700  | 3.6876          | 1.0 |
| 3.0777        | 0.9   | 800  | 3.7421          | 1.0 |
| 2.8181        | 1.01  | 900  | 3.7825          | 1.0 |
| 2.8211        | 1.12  | 1000 | 3.9630          | 1.0 |
| 2.8209        | 1.23  | 1100 | 3.9605          | 1.0 |
| 2.8304        | 1.35  | 1200 | 3.7005          | 1.0 |
| 2.85          | 1.46  | 1300 | 3.5085          | 1.0 |
| 2.8509        | 1.57  | 1400 | 3.6157          | 1.0 |
| 2.8643        | 1.68  | 1500 | 3.5116          | 1.0 |
| 2.8265        | 1.79  | 1600 | 3.6322          | 1.0 |
| 2.8032        | 1.91  | 1700 | 4.0325          | 1.0 |
| 2.8053        | 2.02  | 1800 | 4.0125          | 1.0 |
| 2.819         | 2.13  | 1900 | 3.7971          | 1.0 |
| 2.8163        | 2.24  | 2000 | 3.9216          | 1.0 |
| 2.8214        | 2.35  | 2100 | 3.9178          | 1.0 |
| 2.8116        | 2.47  | 2200 | 3.9604          | 1.0 |
| 2.81          | 2.58  | 2300 | 3.9279          | 1.0 |
| 2.8051        | 2.69  | 2400 | 3.9737          | 1.0 |
| 2.8179        | 2.8   | 2500 | 3.9725          | 1.0 |
| 2.8098        | 2.91  | 2600 | 3.9591          | 1.0 |


### Framework versions

- Transformers 4.12.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.13.4.dev0
- Tokenizers 0.10.3