
<!-- 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. -->

# Whisper Small En - Moh

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the AfriSpeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6236
- Wer: 32.8714

## 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: 1e-05
- 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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.677         | 0.5   | 500  | 0.6841          | 31.2466 |
| 0.428         | 1.0   | 1000 | 0.6236          | 32.8714 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"language": ["en"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "datasets": ["tobiolatunji/afrispeech-200"], "metrics": ["wer"], "model-index": [{"name": "Whisper Small En - Moh", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "AfriSpeech", "type": "tobiolatunji/afrispeech-200", "config": "all", "split": "train", "args": "config: en, split: test"}, "metrics": [{"type": "wer", "value": 32.87142507484043, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer en dataset:tobiolatunji/afrispeech-200 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #en #dataset-tobiolatunji/afrispeech-200 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

Whisper Small En - Moh
======================


This model is a fine-tuned version of openai/whisper-small on the AfriSpeech dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6236
* Wer: 32.8714


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: 1e-05
* 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: 500
* training\_steps: 1000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* 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: 500
* training\_steps: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #en #dataset-tobiolatunji/afrispeech-200 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* 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: 500
* training\_steps: 1000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2