pytorch tensorboard wav2vec2 automatic-speech-recognition dataset:common_voice transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-irish-local
  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. -->

# wav2vec2-large-xls-r-300m-irish-local

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: 2.0788
- Wer: 0.7527

## 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: 50
- num_epochs: 90
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.3839        | 2.94  | 50   | 3.3021          | 1.0    |
| 3.0703        | 5.88  | 100  | 3.1749          | 1.0    |
| 3.1744        | 8.82  | 150  | 3.0452          | 1.0    |
| 2.9719        | 11.76 | 200  | 2.9767          | 1.0    |
| 2.9539        | 14.71 | 250  | 2.9992          | 1.0    |
| 2.9438        | 17.65 | 300  | 2.9767          | 1.0    |
| 2.9296        | 20.59 | 350  | 2.9475          | 1.0    |
| 2.9269        | 23.53 | 400  | 2.9402          | 1.0    |
| 2.9116        | 26.47 | 450  | 2.9255          | 1.0    |
| 2.8326        | 29.41 | 500  | 2.7238          | 1.0    |
| 2.5758        | 32.35 | 550  | 2.3599          | 0.9900 |
| 2.1242        | 35.29 | 600  | 1.8478          | 0.9491 |
| 1.4603        | 38.24 | 650  | 1.5991          | 0.9002 |
| 1.0287        | 41.18 | 700  | 1.5931          | 0.8434 |
| 0.7687        | 44.12 | 750  | 1.6493          | 0.8253 |
| 0.571         | 47.06 | 800  | 1.6889          | 0.8057 |
| 0.4598        | 50.0  | 850  | 1.7521          | 0.7978 |
| 0.3902        | 52.94 | 900  | 1.9074          | 0.7975 |
| 0.318         | 55.88 | 950  | 1.9352          | 0.8133 |
| 0.3026        | 58.82 | 1000 | 2.0157          | 0.8028 |
| 0.2862        | 61.76 | 1050 | 1.9231          | 0.7720 |
| 0.2696        | 64.71 | 1100 | 1.9256          | 0.7644 |
| 0.2528        | 67.65 | 1150 | 2.0277          | 0.7741 |
| 0.2051        | 70.59 | 1200 | 1.9921          | 0.7550 |
| 0.2018        | 73.53 | 1250 | 2.0416          | 0.7615 |
| 0.187         | 76.47 | 1300 | 2.0861          | 0.7635 |
| 0.1749        | 79.41 | 1350 | 2.0926          | 0.7577 |
| 0.1713        | 82.35 | 1400 | 2.0632          | 0.7533 |
| 0.1518        | 85.29 | 1450 | 2.0903          | 0.7542 |
| 0.16          | 88.24 | 1500 | 2.0788          | 0.7527 |


### Framework versions

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