---
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- fleurs
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-oria-v0
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: fleurs
      type: fleurs
      config: or_in
      split: None
      args: or_in
    metrics:
    - type: wer
      value: 0.4972150445018662
      name: Wer
---

<!-- 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-large-xlsr-oria-v0

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6050
- Wer: 0.4972

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 6.6722        | 2.1505  | 100  | 5.4667          | 1.0    |
| 3.4956        | 4.3011  | 200  | 3.4905          | 1.0    |
| 3.4526        | 6.4516  | 300  | 3.4624          | 1.0    |
| 3.4548        | 8.6022  | 400  | 3.4494          | 1.0    |
| 3.4352        | 10.7527 | 500  | 3.4267          | 1.0    |
| 3.0335        | 12.9032 | 600  | 2.8300          | 1.0    |
| 1.021         | 15.0538 | 700  | 0.9941          | 0.7938 |
| 0.6175        | 17.2043 | 800  | 0.7318          | 0.6385 |
| 0.5257        | 19.3548 | 900  | 0.6485          | 0.5820 |
| 0.4232        | 21.5054 | 1000 | 0.6105          | 0.5430 |
| 0.3202        | 23.6559 | 1100 | 0.5906          | 0.5192 |
| 0.2767        | 25.8065 | 1200 | 0.6025          | 0.5079 |
| 0.2679        | 27.9570 | 1300 | 0.6050          | 0.4972 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1