---
license: apache-2.0
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
tags:
- generated_from_trainer
datasets:
- voxpopuli
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-czech-colab-finetuned
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: voxpopuli
      type: voxpopuli
      config: cs
      split: test
      args: cs
    metrics:
    - name: Wer
      type: wer
      value: 0.6178421298458664
---

<!-- 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. -->

# wav2vec2-large-xls-r-300m-czech-colab-finetuned

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: 624.5939
- Wer: 0.6178

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3007.3212     | 3.51  | 100  | 1006.7374       | 0.9865 |
| 354.3011      | 7.02  | 200  | 563.6080        | 0.9980 |
| 211.5289      | 10.53 | 300  | 599.5796        | 0.9165 |
| 187.8653      | 14.04 | 400  | 447.1478        | 0.8099 |
| 163.1056      | 17.54 | 500  | 430.5204        | 0.6875 |
| 143.0342      | 21.05 | 600  | 413.8947        | 0.6850 |
| 116.0388      | 24.56 | 700  | 435.5743        | 0.6737 |
| 95.5554       | 28.07 | 800  | 490.6329        | 0.6339 |
| 80.6966       | 31.58 | 900  | 493.9658        | 0.6344 |
| 68.7335       | 35.09 | 1000 | 525.7507        | 0.6263 |
| 58.3269       | 38.6  | 1100 | 582.5747        | 0.6128 |
| 54.3181       | 42.11 | 1200 | 600.8087        | 0.6308 |
| 48.5287       | 45.61 | 1300 | 594.6959        | 0.6112 |
| 43.041        | 49.12 | 1400 | 624.5939        | 0.6178 |


### Framework versions

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