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

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5532
- Wer: 0.3373
- Cer: 0.1112

## 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: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.1293        | 1.0   | 500   | 0.3918          | 0.3677 | 0.1170 |
| 0.133         | 2.01  | 1000  | 0.4392          | 0.3797 | 0.1234 |
| 0.1473        | 3.01  | 1500  | 0.4959          | 0.3914 | 0.1267 |
| 0.1373        | 4.02  | 2000  | 0.4781          | 0.3851 | 0.1260 |
| 0.1259        | 5.02  | 2500  | 0.4473          | 0.3810 | 0.1237 |
| 0.1123        | 6.02  | 3000  | 0.5314          | 0.3774 | 0.1243 |
| 0.1086        | 7.03  | 3500  | 0.4231          | 0.3801 | 0.1228 |
| 0.0956        | 8.03  | 4000  | 0.5203          | 0.3734 | 0.1236 |
| 0.0839        | 9.04  | 4500  | 0.5310          | 0.3750 | 0.1227 |
| 0.0778        | 10.04 | 5000  | 0.5279          | 0.3793 | 0.1257 |
| 0.0772        | 11.04 | 5500  | 0.4969          | 0.3792 | 0.1265 |
| 0.072         | 12.05 | 6000  | 0.5489          | 0.3701 | 0.1239 |
| 0.0678        | 13.05 | 6500  | 0.5123          | 0.3669 | 0.1207 |
| 0.067         | 14.06 | 7000  | 0.4969          | 0.3663 | 0.1192 |
| 0.061         | 15.06 | 7500  | 0.4742          | 0.3664 | 0.1212 |
| 0.0575        | 16.06 | 8000  | 0.5304          | 0.3643 | 0.1194 |
| 0.0574        | 17.07 | 8500  | 0.4936          | 0.3729 | 0.1218 |
| 0.0474        | 18.07 | 9000  | 0.5363          | 0.3601 | 0.1185 |
| 0.0447        | 19.08 | 9500  | 0.5347          | 0.3552 | 0.1177 |
| 0.0372        | 20.08 | 10000 | 0.5372          | 0.3519 | 0.1157 |
| 0.0325        | 21.08 | 10500 | 0.5455          | 0.3525 | 0.1159 |
| 0.0309        | 22.09 | 11000 | 0.5193          | 0.3514 | 0.1146 |
| 0.0314        | 23.09 | 11500 | 0.5402          | 0.3494 | 0.1160 |
| 0.0272        | 24.1  | 12000 | 0.5309          | 0.3457 | 0.1129 |
| 0.0238        | 25.1  | 12500 | 0.5490          | 0.3447 | 0.1132 |
| 0.0217        | 26.1  | 13000 | 0.5702          | 0.3406 | 0.1117 |
| 0.0225        | 27.11 | 13500 | 0.5575          | 0.3414 | 0.1116 |
| 0.0189        | 28.11 | 14000 | 0.5572          | 0.3391 | 0.1115 |
| 0.0179        | 29.12 | 14500 | 0.5532          | 0.3373 | 0.1112 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3