---
license: apache-2.0
base_model: joorock12/wav2vec2-large-xlsr-italian
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: DynamicWav2Vec_TEST_15
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_1_0
      type: common_voice_1_0
      config: it
      split: test
      args: it
    metrics:
    - name: Wer
      type: wer
      value: 0.19315578954565657
---

<!-- 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. -->

# DynamicWav2Vec_TEST_15

This model is a fine-tuned version of [joorock12/wav2vec2-large-xlsr-italian](https://huggingface.co/joorock12/wav2vec2-large-xlsr-italian) on the common_voice_1_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0991
- Wer: 0.1932

## 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: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2942        | 1.67  | 500  | 0.0745          | 0.1919 |
| 0.2091        | 3.34  | 1000 | 0.0799          | 0.1954 |
| 0.1895        | 5.02  | 1500 | 0.0818          | 0.1958 |
| 0.1673        | 6.69  | 2000 | 0.0891          | 0.1987 |
| 0.1493        | 8.36  | 2500 | 0.0853          | 0.2004 |
| 0.1389        | 10.03 | 3000 | 0.0896          | 0.1982 |
| 0.135         | 11.71 | 3500 | 0.0954          | 0.2023 |
| 0.1246        | 13.38 | 4000 | 0.0947          | 0.1979 |
| 0.1212        | 15.05 | 4500 | 0.0943          | 0.1995 |
| 0.1123        | 16.72 | 5000 | 0.0962          | 0.2001 |
| 0.1073        | 18.39 | 5500 | 0.1025          | 0.2047 |
| 0.1014        | 20.07 | 6000 | 0.1034          | 0.1983 |
| 0.0967        | 21.74 | 6500 | 0.1006          | 0.1976 |
| 0.0968        | 23.41 | 7000 | 0.0969          | 0.1966 |
| 0.092         | 25.08 | 7500 | 0.0980          | 0.1950 |
| 0.0905        | 26.76 | 8000 | 0.0991          | 0.1943 |
| 0.0882        | 28.43 | 8500 | 0.0991          | 0.1932 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1