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# xtreme_s_xlsr_minds14_upd

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the GOOGLE/XTREME_S - MINDS14.FR-FR dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6303
- F1: 0.0223
- Accuracy: 0.0833

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4.dev0
- Tokenizers 0.11.6

{"license": "apache-2.0", "tags": ["minds14", "google/xtreme_s", "generated_from_trainer"], "datasets": ["xtreme_s"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "xtreme_s_xlsr_minds14_upd", "results": []}]}
transformers pytorch tensorboard wav2vec2 audio-classification minds14 google/xtreme_s generated_from_trainer dataset:xtreme_s license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #minds14 #google/xtreme_s #generated_from_trainer #dataset-xtreme_s #license-apache-2.0 #endpoints_compatible #region-us 




# xtreme_s_xlsr_minds14_upd

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME_S - MINDS14.FR-FR dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6303
- F1: 0.0223
- Accuracy: 0.0833

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4.dev0
- Tokenizers 0.11.6

# xtreme_s_xlsr_minds14_upd

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME_S - MINDS14.FR-FR dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6303
- F1: 0.0223
- Accuracy: 0.0833 ## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 3.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4.dev0
- Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #minds14 #google/xtreme_s #generated_from_trainer #dataset-xtreme_s #license-apache-2.0 #endpoints_compatible #region-us 
 # xtreme_s_xlsr_minds14_upd

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME_S - MINDS14.FR-FR dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6303
- F1: 0.0223
- Accuracy: 0.0833 ## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 3.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4.dev0
- Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #minds14 #google/xtreme_s #generated_from_trainer #dataset-xtreme_s #license-apache-2.0 #endpoints_compatible #region-us 
# xtreme_s_xlsr_minds14_upd

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME_S - MINDS14.FR-FR dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6303
- F1: 0.0223
- Accuracy: 0.0833## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 3.0
- mixed_precision_training: Native AMP### Training results### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4.dev0
- Tokenizers 0.11.6