transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer endpoints_compatible region:us
---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_xlsr_finetune_M01-updated
  results: []
---

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# torgo_xlsr_finetune_M01-updated

This model is a fine-tuned version of [macarious/torgo_xlsr_finetune_M01-updated](https://huggingface.co/macarious/torgo_xlsr_finetune_M01-updated) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5724
- Wer: 0.6440

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 26.5318       | 0.45  | 500   | 3.5639          | 1.0    |
| 3.6577        | 0.89  | 1000  | 3.3949          | 1.0    |
| 3.364         | 1.34  | 1500  | 3.2285          | 1.0    |
| 2.5529        | 1.79  | 2000  | 1.9807          | 0.9845 |
| 1.3535        | 2.24  | 2500  | 1.5283          | 0.8922 |
| 0.9851        | 2.68  | 3000  | 1.4430          | 0.8397 |
| 0.7788        | 3.13  | 3500  | 1.3721          | 0.8034 |
| 0.7042        | 3.58  | 4000  | 1.2735          | 0.7897 |
| 0.6514        | 4.03  | 4500  | 1.4396          | 0.7552 |
| 0.546         | 4.47  | 5000  | 1.2647          | 0.7457 |
| 0.5352        | 4.92  | 5500  | 1.2381          | 0.7224 |
| 0.4905        | 5.37  | 6000  | 1.6255          | 0.7164 |
| 0.4444        | 5.81  | 6500  | 1.4475          | 0.7069 |
| 0.4042        | 6.26  | 7000  | 1.6014          | 0.6879 |
| 0.3769        | 6.71  | 7500  | 1.3254          | 0.6879 |
| 0.3685        | 7.16  | 8000  | 1.5400          | 0.6871 |
| 0.3315        | 7.6   | 8500  | 1.4396          | 0.6647 |
| 0.3304        | 8.05  | 9000  | 1.6206          | 0.6707 |
| 0.3083        | 8.5   | 9500  | 1.5340          | 0.6595 |
| 0.2733        | 8.94  | 10000 | 1.5296          | 0.6534 |
| 0.2566        | 9.39  | 10500 | 1.6515          | 0.65   |
| 0.2826        | 9.84  | 11000 | 1.5724          | 0.6440 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.13.3
