---
license: apache-2.0
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
tags:
- generated_from_trainer
datasets:
- nb_samtale
metrics:
- wer
model-index:
- name: cs2no_wav2vec2-large-xls-r-300m-czech-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: nb_samtale
      type: nb_samtale
      config: annotations
      split: test
      args: annotations
    metrics:
    - name: Wer
      type: wer
      value: 0.8457142857142858
---

<!-- 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. -->

# cs2no_wav2vec2-large-xls-r-300m-czech-colab

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 nb_samtale dataset.
It achieves the following results on the evaluation set:
- Loss: 396.8153
- Wer: 0.8457

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3026.3663     | 3.51  | 100  | 472.1026        | 0.9873 |
| 336.2439      | 7.02  | 200  | 239.3806        | 0.9987 |
| 208.6184      | 10.53 | 300  | 206.7293        | 0.9917 |
| 182.6556      | 14.04 | 400  | 221.5585        | 0.8908 |
| 174.3151      | 17.54 | 500  | 262.3953        | 0.8921 |
| 140.57        | 21.05 | 600  | 225.9887        | 0.8330 |
| 114.5967      | 24.56 | 700  | 275.7823        | 0.8495 |
| 91.2748       | 28.07 | 800  | 314.0284        | 0.8610 |
| 80.0496       | 31.58 | 900  | 314.4608        | 0.8552 |
| 66.7338       | 35.09 | 1000 | 326.7965        | 0.8527 |
| 56.921        | 38.6  | 1100 | 373.0237        | 0.8425 |
| 50.7125       | 42.11 | 1200 | 374.9553        | 0.8527 |
| 47.4235       | 45.61 | 1300 | 404.8124        | 0.8489 |
| 45.1623       | 49.12 | 1400 | 396.8153        | 0.8457 |


### Framework versions

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