---
language:
- it
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-it_en-demo
  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-common_voice-it_en-demo

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - IT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1128
- Wer: 0.0947

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.53  | 400  | 1.2299          | 0.7601 |
| 3.6201        | 1.07  | 800  | 0.4973          | 0.4249 |
| 0.6369        | 1.6   | 1200 | 0.3748          | 0.3481 |
| 0.455         | 2.13  | 1600 | 0.2834          | 0.2644 |
| 0.3177        | 2.67  | 2000 | 0.2426          | 0.2234 |
| 0.3177        | 3.2   | 2400 | 0.1868          | 0.1862 |
| 0.2697        | 3.73  | 2800 | 0.1915          | 0.1847 |
| 0.2363        | 4.27  | 3200 | 0.1667          | 0.1608 |
| 0.1795        | 4.8   | 3600 | 0.1458          | 0.1429 |
| 0.1636        | 5.33  | 4000 | 0.1468          | 0.1388 |
| 0.1636        | 5.87  | 4400 | 0.1351          | 0.1314 |
| 0.1445        | 6.4   | 4800 | 0.1163          | 0.1108 |
| 0.1153        | 6.93  | 5200 | 0.1093          | 0.1088 |
| 0.1011        | 7.47  | 5600 | 0.1233          | 0.1141 |
| 0.0978        | 8.0   | 6000 | 0.1147          | 0.1041 |
| 0.0978        | 8.53  | 6400 | 0.1112          | 0.0984 |
| 0.0748        | 9.07  | 6800 | 0.1100          | 0.0938 |
| 0.075         | 9.6   | 7200 | 0.1180          | 0.0960 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.11.0