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_F03
  results: []
---

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# torgo_xlsr_finetune_F03

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: 0.3758
- Wer: 0.1234

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5793        | 1.06  | 1000  | 3.5545          | 1.0    |
| 2.1557        | 2.11  | 2000  | 0.9675          | 0.7402 |
| 0.9155        | 3.17  | 3000  | 0.5581          | 0.4278 |
| 0.6488        | 4.23  | 4000  | 0.4753          | 0.2703 |
| 0.4806        | 5.29  | 5000  | 0.5099          | 0.1864 |
| 0.4012        | 6.34  | 6000  | 0.3734          | 0.1549 |
| 0.3717        | 7.4   | 7000  | 0.4955          | 0.1732 |
| 0.3247        | 8.46  | 8000  | 0.4187          | 0.1339 |
| 0.3028        | 9.51  | 9000  | 0.3920          | 0.1234 |
| 0.2716        | 10.57 | 10000 | 0.6216          | 0.1785 |
| 0.255         | 11.63 | 11000 | 0.3310          | 0.1417 |
| 0.2418        | 12.68 | 12000 | 0.3653          | 0.1339 |
| 0.2111        | 13.74 | 13000 | 0.3677          | 0.1155 |
| 0.1996        | 14.8  | 14000 | 0.4039          | 0.1286 |
| 0.1869        | 15.86 | 15000 | 0.3811          | 0.1339 |
| 0.175         | 16.91 | 16000 | 0.3736          | 0.1286 |
| 0.1651        | 17.97 | 17000 | 0.3848          | 0.1260 |
| 0.179         | 19.03 | 18000 | 0.3758          | 0.1234 |


### Framework versions

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