---
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: 1.0859538784067087
---

<!-- 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: 507.5248
- Wer: 1.0860

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3042.8738     | 3.51  | 100  | 422.1938        | 0.9518 |
| 362.1554      | 7.02  | 200  | 231.7486        | 1.0    |
| 208.092       | 10.53 | 300  | 196.4194        | 0.9958 |
| 189.1354      | 14.04 | 400  | 211.6223        | 0.9350 |
| 163.6355      | 17.54 | 500  | 235.3201        | 0.9182 |
| 140.7959      | 21.05 | 600  | 256.4028        | 0.9539 |
| 115.5506      | 24.56 | 700  | 311.4562        | 1.0147 |
| 93.6629       | 28.07 | 800  | 304.0882        | 1.2243 |
| 78.9694       | 31.58 | 900  | 354.5415        | 1.1279 |
| 67.4151       | 35.09 | 1000 | 423.6178        | 1.0860 |
| 55.1471       | 38.6  | 1100 | 468.3192        | 1.0922 |
| 55.8001       | 42.11 | 1200 | 408.8039        | 1.0839 |
| 46.9208       | 45.61 | 1300 | 524.1367        | 1.0650 |
| 43.7264       | 49.12 | 1400 | 507.5248        | 1.0860 |


### Framework versions

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