---
license: apache-2.0
base_model: facebook/wav2vec2-base-100h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-timit-demo-google-colab
  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-timit-demo-google-colab

This model is a fine-tuned version of [facebook/wav2vec2-base-100h](https://huggingface.co/facebook/wav2vec2-base-100h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1428
- Wer: 0.1265

## 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: 8
- 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: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.924         | 0.26  | 200  | 4.0579          | 1.0    |
| 2.9378        | 0.51  | 400  | 1.9506          | 0.9319 |
| 1.4334        | 0.77  | 600  | 0.7472          | 0.4723 |
| 0.8152        | 1.03  | 800  | 0.5167          | 0.3405 |
| 0.6369        | 1.28  | 1000 | 0.3825          | 0.2747 |
| 0.4931        | 1.54  | 1200 | 0.3361          | 0.2407 |
| 0.4986        | 1.8   | 1400 | 0.3224          | 0.2228 |
| 0.392         | 2.05  | 1600 | 0.2876          | 0.2086 |
| 0.3527        | 2.31  | 1800 | 0.3104          | 0.2089 |
| 0.3171        | 2.57  | 2000 | 0.2431          | 0.1821 |
| 0.2847        | 2.82  | 2200 | 0.2153          | 0.1776 |
| 0.3274        | 3.08  | 2400 | 0.2486          | 0.1679 |
| 0.2901        | 3.34  | 2600 | 0.3754          | 0.1627 |
| 0.2539        | 3.59  | 2800 | 0.2790          | 0.1642 |
| 0.2427        | 3.85  | 3000 | 0.2485          | 0.1664 |
| 0.1992        | 4.11  | 3200 | 0.2184          | 0.1574 |
| 0.2873        | 4.36  | 3400 | 0.1967          | 0.1547 |
| 0.2037        | 4.62  | 3600 | 0.2289          | 0.1506 |
| 0.1967        | 4.88  | 3800 | 0.2263          | 0.1506 |
| 0.2254        | 5.13  | 4000 | 0.1629          | 0.1463 |
| 0.1808        | 5.39  | 4200 | 0.2015          | 0.1476 |
| 0.1762        | 5.65  | 4400 | 0.1948          | 0.1456 |
| 0.1829        | 5.91  | 4600 | 0.1521          | 0.1437 |
| 0.1934        | 6.16  | 4800 | 0.1638          | 0.1431 |
| 0.1643        | 6.42  | 5000 | 0.1476          | 0.1435 |
| 0.1244        | 6.68  | 5200 | 0.1937          | 0.1394 |
| 0.1615        | 6.93  | 5400 | 0.1508          | 0.1366 |
| 0.1708        | 7.19  | 5600 | 0.1298          | 0.1348 |
| 0.1736        | 7.45  | 5800 | 0.1383          | 0.1344 |
| 0.1429        | 7.7   | 6000 | 0.1711          | 0.1330 |
| 0.1453        | 7.96  | 6200 | 0.1844          | 0.1302 |
| 0.1387        | 8.22  | 6400 | 0.3321          | 0.1297 |
| 0.1259        | 8.47  | 6600 | 0.1617          | 0.1296 |
| 0.0874        | 8.73  | 6800 | 0.1432          | 0.1270 |
| 0.1107        | 8.99  | 7000 | 0.1302          | 0.1280 |
| 0.1205        | 9.24  | 7200 | 0.1461          | 0.1270 |
| 0.109         | 9.5   | 7400 | 0.1415          | 0.1271 |
| 0.1117        | 9.76  | 7600 | 0.1428          | 0.1265 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1