---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: tokens
  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. -->

# tokens

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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9811
- Wer: 0.4608

## 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: 16
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.5212        | 0.59  | 400   | 3.3776          | 1.0    |
| 2.4798        | 1.18  | 800   | 1.0697          | 0.7740 |
| 1.0057        | 1.77  | 1200  | 0.7077          | 0.6487 |
| 0.7731        | 2.36  | 1600  | 0.6113          | 0.5883 |
| 0.6917        | 2.94  | 2000  | 0.5618          | 0.5573 |
| 0.5844        | 3.53  | 2400  | 0.5610          | 0.5532 |
| 0.5606        | 4.12  | 2800  | 0.5584          | 0.5484 |
| 0.4973        | 4.71  | 3200  | 0.5466          | 0.5333 |
| 0.4721        | 5.3   | 3600  | 0.5495          | 0.5178 |
| 0.4439        | 5.89  | 4000  | 0.5667          | 0.5237 |
| 0.3965        | 6.48  | 4400  | 0.5865          | 0.5322 |
| 0.3876        | 7.07  | 4800  | 0.6099          | 0.5135 |
| 0.3407        | 7.66  | 5200  | 0.5891          | 0.5228 |
| 0.33          | 8.25  | 5600  | 0.6135          | 0.5072 |
| 0.3032        | 8.84  | 6000  | 0.6004          | 0.5028 |
| 0.2706        | 9.43  | 6400  | 0.6321          | 0.4991 |
| 0.2709        | 10.01 | 6800  | 0.6541          | 0.5051 |
| 0.2373        | 10.6  | 7200  | 0.6613          | 0.5119 |
| 0.2284        | 11.19 | 7600  | 0.6798          | 0.5086 |
| 0.212         | 11.78 | 8000  | 0.6509          | 0.4910 |
| 0.1983        | 12.37 | 8400  | 0.7018          | 0.5043 |
| 0.1947        | 12.96 | 8800  | 0.6826          | 0.4965 |
| 0.1717        | 13.55 | 9200  | 0.7056          | 0.4828 |
| 0.1741        | 14.14 | 9600  | 0.7544          | 0.5060 |
| 0.1626        | 14.73 | 10000 | 0.7331          | 0.4915 |
| 0.1529        | 15.32 | 10400 | 0.7518          | 0.4772 |
| 0.1504        | 15.91 | 10800 | 0.7362          | 0.4732 |
| 0.1401        | 16.49 | 11200 | 0.7179          | 0.4769 |
| 0.1335        | 17.08 | 11600 | 0.7716          | 0.4826 |
| 0.1185        | 17.67 | 12000 | 0.7465          | 0.4798 |
| 0.1182        | 18.26 | 12400 | 0.8105          | 0.4733 |
| 0.1135        | 18.85 | 12800 | 0.7693          | 0.4743 |
| 0.1098        | 19.44 | 13200 | 0.8362          | 0.4888 |
| 0.1023        | 20.03 | 13600 | 0.8427          | 0.4768 |
| 0.1003        | 20.62 | 14000 | 0.8079          | 0.4741 |
| 0.0936        | 21.21 | 14400 | 0.8551          | 0.4651 |
| 0.0875        | 21.8  | 14800 | 0.8462          | 0.4712 |
| 0.0843        | 22.39 | 15200 | 0.9177          | 0.4782 |
| 0.0846        | 22.97 | 15600 | 0.8618          | 0.4735 |
| 0.08          | 23.56 | 16000 | 0.9017          | 0.4687 |
| 0.0789        | 24.15 | 16400 | 0.9034          | 0.4659 |
| 0.0717        | 24.74 | 16800 | 0.9690          | 0.4734 |
| 0.0714        | 25.33 | 17200 | 0.9395          | 0.4677 |
| 0.0699        | 25.92 | 17600 | 0.9222          | 0.4608 |
| 0.0658        | 26.51 | 18000 | 0.9222          | 0.4621 |
| 0.0612        | 27.1  | 18400 | 0.9691          | 0.4586 |
| 0.0583        | 27.69 | 18800 | 0.9647          | 0.4581 |
| 0.0596        | 28.28 | 19200 | 0.9820          | 0.4614 |
| 0.056         | 28.87 | 19600 | 0.9795          | 0.4596 |
| 0.055         | 29.45 | 20000 | 0.9811          | 0.4608 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3