---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-xls-r-300m-west-slavic-cv8
  results: []
---

<!-- 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-xls-r-300m-west-slavic-cv8

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3462
- Wer: 0.8556
- Cer: 0.2799

## 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: 32
- eval_batch_size: 16
- seed: 42
- 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    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 6.548         | 1.23  | 400   | 3.4763          | 1.0    | 1.0    |
| 3.42          | 2.45  | 800   | 3.3156          | 1.0    | 1.0    |
| 3.291         | 3.68  | 1200  | 3.2396          | 1.0    | 1.0    |
| 2.6515        | 4.91  | 1600  | 2.0422          | 0.9997 | 0.5835 |
| 1.7019        | 6.13  | 2000  | 1.6337          | 0.9893 | 0.4797 |
| 1.3604        | 7.36  | 2400  | 1.5221          | 0.9875 | 0.4463 |
| 1.1965        | 8.59  | 2800  | 1.5284          | 0.9766 | 0.4247 |
| 1.069         | 9.82  | 3200  | 1.5228          | 0.9672 | 0.4124 |
| 0.9536        | 11.04 | 3600  | 1.4059          | 0.9600 | 0.3868 |
| 0.8487        | 12.27 | 4000  | 1.4083          | 0.9501 | 0.3739 |
| 0.7655        | 13.5  | 4400  | 1.4079          | 0.9369 | 0.3612 |
| 0.6956        | 14.72 | 4800  | 1.4170          | 0.9411 | 0.3459 |
| 0.6287        | 15.95 | 5200  | 1.4000          | 0.9235 | 0.3384 |
| 0.561         | 17.18 | 5600  | 1.4735          | 0.9023 | 0.3295 |
| 0.5155        | 18.4  | 6000  | 1.5386          | 0.9202 | 0.3223 |
| 0.4864        | 19.63 | 6400  | 1.6186          | 0.9073 | 0.3259 |
| 0.4261        | 20.86 | 6800  | 1.6417          | 0.9217 | 0.3130 |
| 0.4051        | 22.09 | 7200  | 1.6295          | 0.8954 | 0.3026 |
| 0.3779        | 23.31 | 7600  | 1.8218          | 0.8979 | 0.3153 |
| 0.35          | 24.54 | 8000  | 1.7790          | 0.8921 | 0.3036 |
| 0.3343        | 25.77 | 8400  | 1.8588          | 0.9114 | 0.3072 |
| 0.3137        | 26.99 | 8800  | 1.8096          | 0.8756 | 0.2935 |
| 0.299         | 28.22 | 9200  | 1.9721          | 0.8863 | 0.3023 |
| 0.2894        | 29.45 | 9600  | 1.9907          | 0.8872 | 0.2958 |
| 0.2784        | 30.67 | 10000 | 1.9494          | 0.9090 | 0.2945 |
| 0.2662        | 31.9  | 10400 | 1.9952          | 0.8978 | 0.2935 |
| 0.2614        | 33.13 | 10800 | 2.0600          | 0.8949 | 0.2979 |
| 0.2401        | 34.36 | 11200 | 2.1180          | 0.8914 | 0.2950 |
| 0.2392        | 35.58 | 11600 | 2.1197          | 0.8713 | 0.2895 |
| 0.23          | 36.81 | 12000 | 2.1680          | 0.8713 | 0.2941 |
| 0.2246        | 38.04 | 12400 | 2.1526          | 0.8741 | 0.2879 |
| 0.2152        | 39.26 | 12800 | 2.2631          | 0.8790 | 0.2889 |
| 0.212         | 40.49 | 13200 | 2.2724          | 0.8661 | 0.2843 |
| 0.2044        | 41.72 | 13600 | 2.2438          | 0.8691 | 0.2878 |
| 0.2029        | 42.94 | 14000 | 2.2519          | 0.8577 | 0.2833 |
| 0.1972        | 44.17 | 14400 | 2.2697          | 0.8604 | 0.2813 |
| 0.1884        | 45.4  | 14800 | 2.3294          | 0.8662 | 0.2847 |
| 0.1877        | 46.63 | 15200 | 2.3077          | 0.8561 | 0.2793 |
| 0.1871        | 47.85 | 15600 | 2.3518          | 0.8563 | 0.2801 |
| 0.1838        | 49.08 | 16000 | 2.3462          | 0.8556 | 0.2799 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0