
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-nepali-rikeshsilwal

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: 0.3282
- Wer: 0.4024

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2477        | 17.09 | 1000 | 0.2943          | 0.4475 |
| 0.0974        | 34.19 | 2000 | 0.3282          | 0.4024 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- Datasets 1.18.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-nepali-rikeshsilwal", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible has_space region:us