---
language:
- ga-IE
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
  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. -->

# 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - GA-IE dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:---:|
| 3.0395        | 1.94  | 500   | 3.0831          | 1.0 |
| 3.0126        | 3.87  | 1000  | 2.9935          | 1.0 |
| 2.9259        | 5.81  | 1500  | 2.9915          | 1.0 |
| 2.9109        | 7.75  | 2000  | 2.9006          | 1.0 |
| 2.8934        | 9.69  | 2500  | 2.9266          | 1.0 |
| 2.9014        | 11.63 | 3000  | 2.8970          | 1.0 |
| 2.8932        | 13.56 | 3500  | 2.8874          | 1.0 |
| 0.0           | 15.5  | 4000  | nan             | 1.0 |
| 0.0           | 17.44 | 4500  | nan             | 1.0 |
| 0.0           | 19.38 | 5000  | nan             | 1.0 |
| 0.0           | 21.32 | 5500  | nan             | 1.0 |
| 0.0           | 23.26 | 6000  | nan             | 1.0 |
| 0.0           | 25.19 | 6500  | nan             | 1.0 |
| 0.0           | 27.13 | 7000  | nan             | 1.0 |
| 0.0           | 29.07 | 7500  | nan             | 1.0 |
| 0.0           | 31.01 | 8000  | nan             | 1.0 |
| 0.0           | 32.94 | 8500  | nan             | 1.0 |
| 0.0           | 34.88 | 9000  | nan             | 1.0 |
| 0.0           | 36.82 | 9500  | nan             | 1.0 |
| 0.0           | 38.76 | 10000 | nan             | 1.0 |
| 0.0           | 40.7  | 10500 | nan             | 1.0 |
| 0.0           | 42.63 | 11000 | nan             | 1.0 |
| 0.0           | 44.57 | 11500 | nan             | 1.0 |
| 0.0           | 46.51 | 12000 | nan             | 1.0 |
| 0.0           | 48.45 | 12500 | nan             | 1.0 |
| 0.0           | 50.39 | 13000 | nan             | 1.0 |
| 0.0           | 52.32 | 13500 | nan             | 1.0 |
| 0.0           | 54.26 | 14000 | nan             | 1.0 |
| 0.0           | 56.2  | 14500 | nan             | 1.0 |
| 0.0           | 58.14 | 15000 | nan             | 1.0 |
| 0.0           | 60.08 | 15500 | nan             | 1.0 |
| 0.0           | 62.02 | 16000 | nan             | 1.0 |
| 0.0           | 63.95 | 16500 | nan             | 1.0 |
| 0.0           | 65.89 | 17000 | nan             | 1.0 |
| 0.0           | 67.83 | 17500 | nan             | 1.0 |
| 0.0           | 69.77 | 18000 | nan             | 1.0 |
| 0.0           | 71.7  | 18500 | nan             | 1.0 |
| 0.0           | 73.64 | 19000 | nan             | 1.0 |
| 0.0           | 75.58 | 19500 | nan             | 1.0 |
| 0.0           | 77.52 | 20000 | nan             | 1.0 |
| 0.0           | 79.46 | 20500 | nan             | 1.0 |
| 0.0           | 81.39 | 21000 | nan             | 1.0 |
| 0.0           | 83.33 | 21500 | nan             | 1.0 |
| 0.0           | 85.27 | 22000 | nan             | 1.0 |
| 0.0           | 87.21 | 22500 | nan             | 1.0 |
| 0.0           | 89.15 | 23000 | nan             | 1.0 |
| 0.0           | 91.09 | 23500 | nan             | 1.0 |
| 0.0           | 93.02 | 24000 | nan             | 1.0 |
| 0.0           | 94.96 | 24500 | nan             | 1.0 |
| 0.0           | 96.9  | 25000 | nan             | 1.0 |
| 0.0           | 98.83 | 25500 | nan             | 1.0 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0