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_M04
  results: []
---

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# torgo_xlsr_finetune_M04

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6215
- Wer: 0.2742

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4822        | 0.84  | 1000  | 3.2714          | 1.0    |
| 1.8117        | 1.69  | 2000  | 1.6545          | 0.7980 |
| 0.8407        | 2.53  | 3000  | 1.4796          | 0.5925 |
| 0.6096        | 3.38  | 4000  | 1.3550          | 0.5331 |
| 0.4956        | 4.22  | 5000  | 1.4899          | 0.4576 |
| 0.4388        | 5.07  | 6000  | 1.1873          | 0.3778 |
| 0.374         | 5.91  | 7000  | 1.2894          | 0.3591 |
| 0.3569        | 6.76  | 8000  | 1.2815          | 0.3336 |
| 0.2865        | 7.6   | 9000  | 1.3162          | 0.3073 |
| 0.2809        | 8.45  | 10000 | 1.4108          | 0.3234 |
| 0.2455        | 9.29  | 11000 | 1.3710          | 0.2920 |
| 0.2266        | 10.14 | 12000 | 1.4937          | 0.2946 |
| 0.2368        | 10.98 | 13000 | 1.5300          | 0.3056 |
| 0.2229        | 11.82 | 14000 | 1.3822          | 0.2683 |
| 0.1929        | 12.67 | 15000 | 1.4279          | 0.2683 |
| 0.1823        | 13.51 | 16000 | 1.5015          | 0.2869 |
| 0.1678        | 14.36 | 17000 | 1.7070          | 0.3048 |
| 0.1751        | 15.2  | 18000 | 1.4764          | 0.2844 |
| 0.1682        | 16.05 | 19000 | 1.2581          | 0.2742 |
| 0.1607        | 16.89 | 20000 | 1.5641          | 0.2852 |
| 0.1431        | 17.74 | 21000 | 1.6488          | 0.2742 |
| 0.1442        | 18.58 | 22000 | 1.5386          | 0.2725 |
| 0.1147        | 19.43 | 23000 | 1.6215          | 0.2742 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.13.3
