---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-ha-cv8
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-large-xls-r-300m-ha-cv8

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: 0.6094
- Wer: 0.5234

## 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: 16
- eval_batch_size: 8
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9599        | 6.56  | 400  | 2.8650          | 1.0    |
| 2.7357        | 13.11 | 800  | 2.7377          | 0.9951 |
| 1.3012        | 19.67 | 1200 | 0.6686          | 0.7111 |
| 1.0454        | 26.23 | 1600 | 0.5686          | 0.6137 |
| 0.9069        | 32.79 | 2000 | 0.5576          | 0.5815 |
| 0.82          | 39.34 | 2400 | 0.5502          | 0.5591 |
| 0.7413        | 45.9  | 2800 | 0.5970          | 0.5586 |
| 0.6872        | 52.46 | 3200 | 0.5817          | 0.5428 |
| 0.634         | 59.02 | 3600 | 0.5636          | 0.5314 |
| 0.6022        | 65.57 | 4000 | 0.5780          | 0.5229 |
| 0.5705        | 72.13 | 4400 | 0.6036          | 0.5323 |
| 0.5408        | 78.69 | 4800 | 0.6119          | 0.5336 |
| 0.5225        | 85.25 | 5200 | 0.6105          | 0.5270 |
| 0.5265        | 91.8  | 5600 | 0.6034          | 0.5231 |
| 0.5154        | 98.36 | 6000 | 0.6094          | 0.5234 |


### Framework versions

- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0