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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: 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
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