---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-nsc-demo-3
  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-3

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: 0.4681
- Wer: 0.1933

## 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: 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6872        | 2.27  | 50   | 0.3920          | 0.2365 |
| 0.3487        | 4.55  | 100  | 0.3700          | 0.2129 |
| 0.2121        | 6.82  | 150  | 0.4308          | 0.2202 |
| 0.1737        | 9.09  | 200  | 0.4114          | 0.2051 |
| 0.1378        | 11.36 | 250  | 0.4674          | 0.2084 |
| 0.114         | 13.64 | 300  | 0.4989          | 0.2162 |
| 0.0885        | 15.91 | 350  | 0.4914          | 0.1998 |
| 0.097         | 18.18 | 400  | 0.4597          | 0.1986 |
| 0.0694        | 20.45 | 450  | 0.4933          | 0.1996 |
| 0.0747        | 22.73 | 500  | 0.4690          | 0.1963 |
| 0.0792        | 25.0  | 550  | 0.4619          | 0.1963 |
| 0.0646        | 27.27 | 600  | 0.4691          | 0.1951 |
| 0.0604        | 29.55 | 650  | 0.4681          | 0.1933 |


### Framework versions

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