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_M05
  results: []
---

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# torgo_xlsr_finetune_M05

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: 1.7932
- Wer: 0.3577

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5534        | 0.99  | 1000  | 3.4455          | 1.0    |
| 2.3481        | 1.98  | 2000  | 1.8194          | 0.8971 |
| 0.9664        | 2.97  | 3000  | 1.2685          | 0.6818 |
| 0.672         | 3.96  | 4000  | 1.3412          | 0.6112 |
| 0.5432        | 4.96  | 5000  | 1.4455          | 0.5275 |
| 0.4393        | 5.95  | 6000  | 1.3948          | 0.4761 |
| 0.3761        | 6.94  | 7000  | 1.8967          | 0.4785 |
| 0.3474        | 7.93  | 8000  | 1.5481          | 0.4545 |
| 0.309         | 8.92  | 9000  | 1.7275          | 0.4354 |
| 0.284         | 9.91  | 10000 | 1.9297          | 0.4438 |
| 0.2582        | 10.9  | 11000 | 1.4894          | 0.3971 |
| 0.2426        | 11.89 | 12000 | 1.6811          | 0.3840 |
| 0.2406        | 12.88 | 13000 | 1.7411          | 0.3935 |
| 0.2281        | 13.88 | 14000 | 1.7894          | 0.3732 |
| 0.1874        | 14.87 | 15000 | 1.7728          | 0.3864 |
| 0.1918        | 15.86 | 16000 | 2.0315          | 0.3768 |
| 0.1693        | 16.85 | 17000 | 1.7024          | 0.3672 |
| 0.1551        | 17.84 | 18000 | 1.7620          | 0.3684 |
| 0.1645        | 18.83 | 19000 | 1.7186          | 0.3696 |
| 0.1527        | 19.82 | 20000 | 1.7932          | 0.3577 |


### Framework versions

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