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_F04
  results: []
---

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# torgo_xlsr_finetune_F04

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: 1.6313
- Wer: 0.3274

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5075        | 0.95  | 1000  | 3.3352          | 1.0    |
| 1.8254        | 1.89  | 2000  | 1.7412          | 0.8714 |
| 0.8749        | 2.84  | 3000  | 1.5034          | 0.6508 |
| 0.6621        | 3.78  | 4000  | 1.8431          | 0.5925 |
| 0.5211        | 4.73  | 5000  | 1.4749          | 0.4916 |
| 0.4321        | 5.68  | 6000  | 1.4354          | 0.4748 |
| 0.3739        | 6.62  | 7000  | 1.5245          | 0.4580 |
| 0.3332        | 7.57  | 8000  | 1.5774          | 0.4550 |
| 0.3028        | 8.51  | 9000  | 1.6406          | 0.3887 |
| 0.2828        | 9.46  | 10000 | 1.4622          | 0.3867 |
| 0.2588        | 10.41 | 11000 | 1.5811          | 0.3689 |
| 0.2522        | 11.35 | 12000 | 1.6337          | 0.3739 |
| 0.2303        | 12.3  | 13000 | 1.5185          | 0.3531 |
| 0.2249        | 13.24 | 14000 | 1.4798          | 0.3521 |
| 0.2002        | 14.19 | 15000 | 1.9813          | 0.3818 |
| 0.1924        | 15.14 | 16000 | 1.8237          | 0.3709 |
| 0.1824        | 16.08 | 17000 | 1.6372          | 0.3373 |
| 0.1628        | 17.03 | 18000 | 1.8213          | 0.3482 |
| 0.1652        | 17.97 | 19000 | 1.6352          | 0.3403 |
| 0.1521        | 18.92 | 20000 | 1.6690          | 0.3383 |
| 0.1564        | 19.87 | 21000 | 1.6313          | 0.3274 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.13.3
