
<!-- 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 Romanian

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 Romanian Dataset dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2164
- eval_wer: 94.3222
- eval_runtime: 2993.0092
- eval_samples_per_second: 1.289
- eval_steps_per_second: 0.161
- epoch: 1.8
- step: 1000

## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"language": ["ro"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "model-index": [{"name": "Whisper Small Romanian", "results": []}]}
transformers pytorch tensorboard whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ro dataset:mozilla-foundation/common_voice_11_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #ro #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #endpoints_compatible #region-us 




# Whisper Small Romanian

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 Romanian Dataset dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2164
- eval_wer: 94.3222
- eval_runtime: 2993.0092
- eval_samples_per_second: 1.289
- eval_steps_per_second: 0.161
- epoch: 1.8
- step: 1000

## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

# Whisper Small Romanian

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 Romanian Dataset dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2164
- eval_wer: 94.3222
- eval_runtime: 2993.0092
- eval_samples_per_second: 1.289
- eval_steps_per_second: 0.161
- epoch: 1.8
- step: 1000 ## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #ro #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #endpoints_compatible #region-us 
 # Whisper Small Romanian

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 Romanian Dataset dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2164
- eval_wer: 94.3222
- eval_runtime: 2993.0092
- eval_samples_per_second: 1.289
- eval_steps_per_second: 0.161
- epoch: 1.8
- step: 1000 ## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #ro #dataset-mozilla-foundation/common_voice_11_0 #license-apache-2.0 #endpoints_compatible #region-us 
# Whisper Small Romanian

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 Romanian Dataset dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.2164
- eval_wer: 94.3222
- eval_runtime: 2993.0092
- eval_samples_per_second: 1.289
- eval_steps_per_second: 0.161
- epoch: 1.8
- step: 1000## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3