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---
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
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