---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: DynamicWav2Vec_TEST_10
  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: 1.0
---

<!-- 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_10

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_1_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9344
- Wer: 1.0

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 3.5792        | 2.68  | 400  | 2.9642          | 1.0 |
| 2.9539        | 5.35  | 800  | 2.9882          | 1.0 |
| 2.9476        | 8.03  | 1200 | 3.0384          | 1.0 |
| 2.9497        | 10.7  | 1600 | 2.9524          | 1.0 |
| 2.9562        | 13.38 | 2000 | 2.9332          | 1.0 |
| 2.945         | 16.05 | 2400 | 2.9858          | 1.0 |
| 2.9383        | 18.73 | 2800 | 2.9419          | 1.0 |
| 2.9311        | 21.4  | 3200 | 2.9328          | 1.0 |
| 2.9298        | 24.08 | 3600 | 2.9375          | 1.0 |
| 2.9273        | 26.76 | 4000 | 2.9352          | 1.0 |
| 2.921         | 29.43 | 4400 | 2.9344          | 1.0 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3