transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_13_0 base_model:infinitejoy/wav2vec2-large-xls-r-300m-sakha license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: infinitejoy/wav2vec2-large-xls-r-300m-sakha
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-sakha-yaksaha
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: sah
      split: test
      args: sah
    metrics:
    - name: Wer
      type: wer
      value: 0.5587892898719441
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-large-xls-r-300m-sakha-yaksaha

This model is a fine-tuned version of [infinitejoy/wav2vec2-large-xls-r-300m-sakha](https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-sakha) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5156
- Wer: 0.5588

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.4   | 40   | 0.6200          | 0.6082 |
| 1.0278        | 2.81  | 80   | 0.5563          | 0.6026 |
| 0.648         | 4.21  | 120  | 0.5401          | 0.5763 |
| 0.5401        | 5.61  | 160  | 0.5424          | 0.5824 |
| 0.4972        | 7.02  | 200  | 0.5232          | 0.5638 |
| 0.4972        | 8.42  | 240  | 0.5022          | 0.5528 |
| 0.467         | 9.82  | 280  | 0.5156          | 0.5588 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
