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---
license: apache-2.0
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
tags:
- generated_from_trainer
datasets:
- nb_samtale
metrics:
- wer
model-index:
- name: cs2no_wav2vec2-large-xls-r-300m-czech-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: nb_samtale
type: nb_samtale
config: annotations
split: test
args: annotations
metrics:
- name: Wer
type: wer
value: 0.8457142857142858
---
<!-- 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. -->
# cs2no_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 nb_samtale dataset.
It achieves the following results on the evaluation set:
- Loss: 396.8153
- Wer: 0.8457
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3026.3663 | 3.51 | 100 | 472.1026 | 0.9873 |
| 336.2439 | 7.02 | 200 | 239.3806 | 0.9987 |
| 208.6184 | 10.53 | 300 | 206.7293 | 0.9917 |
| 182.6556 | 14.04 | 400 | 221.5585 | 0.8908 |
| 174.3151 | 17.54 | 500 | 262.3953 | 0.8921 |
| 140.57 | 21.05 | 600 | 225.9887 | 0.8330 |
| 114.5967 | 24.56 | 700 | 275.7823 | 0.8495 |
| 91.2748 | 28.07 | 800 | 314.0284 | 0.8610 |
| 80.0496 | 31.58 | 900 | 314.4608 | 0.8552 |
| 66.7338 | 35.09 | 1000 | 326.7965 | 0.8527 |
| 56.921 | 38.6 | 1100 | 373.0237 | 0.8425 |
| 50.7125 | 42.11 | 1200 | 374.9553 | 0.8527 |
| 47.4235 | 45.61 | 1300 | 404.8124 | 0.8489 |
| 45.1623 | 49.12 | 1400 | 396.8153 | 0.8457 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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