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# wav2vec2-xlsr-et-lm-1B

This model was finetuned with mozilla_foundation/common_voice_8_0 et with train+other+validation splits.
It achieves the following results on the test set:
(Loss reported with last eval step at step 2000/2040 during training)
- Loss: 0.2150 
- Wer: 0.2012

## 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: 0.00005
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 1
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results




### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0

{"language": "et", "tags": ["generated_from_trainer", "mozilla-foundation/common_voice_8_0", "audio", "automatic-speech-recognition", "speech", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "metrics": ["wer", "cer"], "model-index": [{"name": "XLS-R 1B Wav2Vec2 Estonian by Rasmus Toivanen", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Common Voice 8", "type": "mozilla-foundation/common_voice_8_0", "args": "et"}, "metrics": [{"type": "wer", "value": 20.12, "name": "Test WER"}, {"type": "cer", "value": 3.82, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "et"}, "metrics": [{"type": "wer", "value": 40.77, "name": "Test WER"}, {"type": "cer", "value": 12.32, "name": "Test CER"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Test Data", "type": "speech-recognition-community-v2/eval_data", "args": "et"}, "metrics": [{"type": "wer", "value": 41.97, "name": "Test WER"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer mozilla-foundation/common_voice_8_0 audio speech robust-speech-event hf-asr-leaderboard et dataset:mozilla-foundation/common_voice_8_0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_8_0 #audio #speech #robust-speech-event #hf-asr-leaderboard #et #dataset-mozilla-foundation/common_voice_8_0 #model-index #endpoints_compatible #region-us 


# wav2vec2-xlsr-et-lm-1B

This model was finetuned with mozilla_foundation/common_voice_8_0 et with train+other+validation splits.
It achieves the following results on the test set:
(Loss reported with last eval step at step 2000/2040 during training)
- Loss: 0.2150 
- Wer: 0.2012

## 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: 0.00005
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 1
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results




### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0

# wav2vec2-xlsr-et-lm-1B

This model was finetuned with mozilla_foundation/common_voice_8_0 et with train+other+validation splits.
It achieves the following results on the test set:
(Loss reported with last eval step at step 2000/2040 during training)
- Loss: 0.2150 
- Wer: 0.2012 ## 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: 0.00005
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 1
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_8_0 #audio #speech #robust-speech-event #hf-asr-leaderboard #et #dataset-mozilla-foundation/common_voice_8_0 #model-index #endpoints_compatible #region-us 
 # wav2vec2-xlsr-et-lm-1B

This model was finetuned with mozilla_foundation/common_voice_8_0 et with train+other+validation splits.
It achieves the following results on the test set:
(Loss reported with last eval step at step 2000/2040 during training)
- Loss: 0.2150 
- Wer: 0.2012 ## 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: 0.00005
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 1
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #mozilla-foundation/common_voice_8_0 #audio #speech #robust-speech-event #hf-asr-leaderboard #et #dataset-mozilla-foundation/common_voice_8_0 #model-index #endpoints_compatible #region-us 
# wav2vec2-xlsr-et-lm-1B

This model was finetuned with mozilla_foundation/common_voice_8_0 et with train+other+validation splits.
It achieves the following results on the test set:
(Loss reported with last eval step at step 2000/2040 during training)
- Loss: 0.2150 
- Wer: 0.2012## 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: 0.00005
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 1
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP### Training results### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0