transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_xlsr_finetune_M03
  results: []
---

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# torgo_xlsr_finetune_M03

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6993
- Wer: 0.3247

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5549        | 0.94  | 1000  | 3.3500          | 1.0    |
| 1.6884        | 1.89  | 2000  | 1.7291          | 0.8173 |
| 0.8237        | 2.83  | 3000  | 1.4608          | 0.6568 |
| 0.6483        | 3.77  | 4000  | 1.1613          | 0.4954 |
| 0.5299        | 4.72  | 5000  | 1.5725          | 0.4824 |
| 0.4091        | 5.66  | 6000  | 1.4437          | 0.4685 |
| 0.3694        | 6.6   | 7000  | 1.4507          | 0.4397 |
| 0.3515        | 7.55  | 8000  | 1.4397          | 0.4230 |
| 0.2878        | 8.49  | 9000  | 1.4089          | 0.3980 |
| 0.2698        | 9.43  | 10000 | 1.4696          | 0.3776 |
| 0.2621        | 10.38 | 11000 | 1.6717          | 0.3905 |
| 0.2465        | 11.32 | 12000 | 1.6235          | 0.3544 |
| 0.221         | 12.26 | 13000 | 1.4009          | 0.3479 |
| 0.2169        | 13.21 | 14000 | 1.6981          | 0.3636 |
| 0.187         | 14.15 | 15000 | 1.4411          | 0.3302 |
| 0.1918        | 15.09 | 16000 | 1.6418          | 0.3377 |
| 0.1876        | 16.04 | 17000 | 1.4613          | 0.3340 |
| 0.1641        | 16.98 | 18000 | 1.6040          | 0.3312 |
| 0.1546        | 17.92 | 19000 | 1.6096          | 0.3293 |
| 0.1522        | 18.87 | 20000 | 1.7270          | 0.3265 |
| 0.1332        | 19.81 | 21000 | 1.6993          | 0.3247 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3
