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---
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
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