transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:voxpopuli base_model:facebook/wav2vec2-lv-60-espeak-cv-ft license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
tags:
- generated_from_trainer
datasets:
- voxpopuli
metrics:
- wer
model-index:
- name: cs2fi-wav2vec2-large-xls-r-300m-cs-colab-phoneme
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: voxpopuli
      type: voxpopuli
      config: fi
      split: test
      args: fi
    metrics:
    - name: Wer
      type: wer
      value: 0.5253440751930178
---

<!-- 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. -->

# cs2fi-wav2vec2-large-xls-r-300m-cs-colab-phoneme

This model is a fine-tuned version of [facebook/wav2vec2-lv-60-espeak-cv-ft](https://huggingface.co/facebook/wav2vec2-lv-60-espeak-cv-ft) on the voxpopuli dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2508
- Wer: 0.5253

## 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
- 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: 500
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.8061        | 16.67 | 100  | 2.7437          | 0.5693 |
| 2.871         | 33.33 | 200  | 2.4209          | 0.5314 |
| 2.525         | 50.0  | 300  | 2.2508          | 0.5253 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
