---
language:
- en_us
license: apache-2.0
tags:
- fleurs-asr
- google/xtreme_s
- generated_from_trainer
datasets:
- google/xtreme_s
model-index:
- name: xtreme_s_xlsr_300m_fleurs_asr_en_us
  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. -->

# xtreme_s_xlsr_300m_fleurs_asr_en_us

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the GOOGLE/XTREME_S - FLEURS.EN_US dataset.
It achieves the following results on the evaluation set:
- Cer: 0.1356
- Loss: 0.5599
- Wer: 0.3148
- Predict Samples: 647

## 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: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 2.8769        | 5.0   | 200  | 2.8871          | 1.0    | 0.9878 |
| 0.2458        | 10.0  | 400  | 0.5570          | 0.4899 | 0.1951 |
| 0.0762        | 15.0  | 600  | 0.5213          | 0.3727 | 0.1562 |
| 0.0334        | 20.0  | 800  | 0.5742          | 0.3666 | 0.1543 |
| 0.0244        | 25.0  | 1000 | 0.5907          | 0.3546 | 0.1499 |
| 0.0143        | 30.0  | 1200 | 0.5961          | 0.3460 | 0.1469 |


### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.10.1+cu111
- Datasets 1.18.4.dev0
- Tokenizers 0.11.6