---
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-czech-colab
  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: 1.0754716981132075
---

<!-- 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-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 voxpopuli dataset.
It achieves the following results on the evaluation set:
- Loss: 485.7458
- Wer: 1.0755

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3007.5297     | 3.51  | 100  | 523.8923        | 0.9706 |
| 353.1859      | 7.02  | 200  | 270.8087        | 0.9665 |
| 207.1084      | 10.53 | 300  | 215.3542        | 0.9350 |
| 186.3063      | 14.04 | 400  | 210.1422        | 0.9119 |
| 171.7259      | 17.54 | 500  | 291.5182        | 1.0629 |
| 142.6091      | 21.05 | 600  | 219.2806        | 0.9602 |
| 118.6791      | 24.56 | 700  | 312.2755        | 1.1132 |
| 96.153        | 28.07 | 800  | 320.7119        | 1.0545 |
| 82.968        | 31.58 | 900  | 357.5117        | 1.0629 |
| 71.2426       | 35.09 | 1000 | 421.3889        | 0.9916 |
| 58.8083       | 38.6  | 1100 | 433.8375        | 1.1048 |
| 54.5225       | 42.11 | 1200 | 482.5988        | 1.0566 |
| 48.12         | 45.61 | 1300 | 479.3787        | 1.0860 |
| 43.3324       | 49.12 | 1400 | 485.7458        | 1.0755 |


### Framework versions

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