pytorch tensorboard wav2vec2 automatic-speech-recognition transformers generated_from_trainer model-index
---
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-en-in
  results: []
---

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# wav2vec2-base-en-in

This model is a fine-tuned version of [beinghorizontal/wav2vec2-base-en-in](https://huggingface.co/beinghorizontal/wav2vec2-base-en-in) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.4400
- eval_wer: 0.2424
- eval_runtime: 28.5705
- eval_samples_per_second: 8.365
- eval_steps_per_second: 1.05
- epoch: 27.78
- step: 2500

## 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: 100
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.17.0
- Pytorch 1.12.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
