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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-mk
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: fleurs
config: mk_mk
split: test
args: mk_mk
metrics:
- name: Wer
type: wer
value: 0.14327357528057136
---
<!-- 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-mk
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on Macedonian
using the train and validation splits of the FLEURS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1589
- Wer: 0.1433
## 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.609 | 2.33 | 400 | 0.3751 | 0.4184 |
| 0.232 | 4.65 | 800 | 0.1694 | 0.1960 |
| 0.0773 | 6.98 | 1200 | 0.1630 | 0.1598 |
| 0.0407 | 9.3 | 1600 | 0.1589 | 0.1433 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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