---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-nsc-demo-4
  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. -->

# wav2vec2-base-nsc-demo-4

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3016
- Wer: 0.1720

## 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: 5.9591386586384804e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 51

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7542        | 2.27  | 50   | 0.3351          | 0.1948 |
| 0.3912        | 4.55  | 100  | 0.3016          | 0.1720 |
| 0.2497        | 6.82  | 150  | 0.3247          | 0.1757 |
| 0.201         | 9.09  | 200  | 0.3111          | 0.1728 |
| 0.1602        | 11.36 | 250  | 0.3259          | 0.1723 |
| 0.1334        | 13.64 | 300  | 0.3431          | 0.1765 |
| 0.1083        | 15.91 | 350  | 0.3413          | 0.1726 |
| 0.1114        | 18.18 | 400  | 0.4089          | 0.1768 |
| 0.0828        | 20.45 | 450  | 0.3531          | 0.1765 |
| 0.0926        | 22.73 | 500  | 0.3481          | 0.1755 |
| 0.093         | 25.0  | 550  | 0.3379          | 0.1742 |
| 0.0772        | 27.27 | 600  | 0.3628          | 0.1779 |
| 0.0701        | 29.55 | 650  | 0.3747          | 0.1773 |
| 0.0736        | 31.82 | 700  | 0.3834          | 0.1808 |
| 0.0607        | 34.09 | 750  | 0.3747          | 0.1742 |
| 0.0629        | 36.36 | 800  | 0.3683          | 0.1734 |
| 0.0713        | 38.64 | 850  | 0.3671          | 0.1744 |
| 0.0728        | 40.91 | 900  | 0.3632          | 0.1749 |
| 0.0696        | 43.18 | 950  | 0.3615          | 0.1731 |
| 0.0638        | 45.45 | 1000 | 0.3591          | 0.1755 |
| 0.0552        | 47.73 | 1050 | 0.3608          | 0.1779 |
| 0.0578        | 50.0  | 1100 | 0.3630          | 0.1752 |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3