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# Fi2Hr-wav2vec2-large-xls-r-300m-finnish-colab

This model was trained from scratch on the voxpopuli dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5849
- Wer: 0.9766

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4545        | 10.67 | 800  | 2.4336          | 0.9655 |
| 0.1599        | 21.33 | 1600 | 2.8208          | 0.9692 |
| 0.0758        | 32.0  | 2400 | 3.5207          | 0.9803 |
| 0.0405        | 42.67 | 3200 | 3.5849          | 0.9766 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "datasets": ["voxpopuli"], "metrics": ["wer"], "model-index": [{"name": "Fi2Hr-wav2vec2-large-xls-r-300m-finnish-colab", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "voxpopuli", "type": "voxpopuli", "config": "hr", "split": "test", "args": "hr"}, "metrics": [{"type": "wer", "value": 0.9765721331689272, "name": "Wer"}]}]}]}
transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:voxpopuli model-index endpoints_compatible region:us