
<!-- 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. -->

# asr-amharic-phoneme-based

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.9967
- eval_wer: 0.1463
- eval_runtime: 22.6834
- eval_samples_per_second: 15.827
- eval_steps_per_second: 1.984
- epoch: 18.82
- step: 6400

## 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: 5e-05
- train_batch_size: 32
- 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: 20

### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "facebook/wav2vec2-base", "model-index": [{"name": "asr-amharic-phoneme-based", "results": []}]}
transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:facebook/wav2vec2-base license:apache-2.0 endpoints_compatible region:us