---
language:
- hu
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- hu
- robust-speech-event
- model_for_talk
datasets:
- mozilla-foundation/common_voice_7_0

model-index:
- name: Akashpb13/xlsr_hungarian_new
  results:
  - task: 
      name: Automatic Speech Recognition 
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 7
      type: mozilla-foundation/common_voice_7_0
      args: hu
    metrics:
       - name: Test WER
         type: wer
         value: 0.02698525418772714
       - name: Test CER
         type: cer
         value: 0.005033063261641211
  - task: 
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Robust Speech Event - Dev Data
      type: speech-recognition-community-v2/dev_data
      args: hu
    metrics:
       - name: Test WER
         type: wer
         value: 0.02698525418772714
       - name: Test CER
         type: cer
         value: 0.005033063261641211
---

# Akashpb13/xlsr_hungarian_new

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset.
It achieves the following results on evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other, dev and validated datasets):
- Loss: 0.184265
- Wer: 0.292771
## 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: 0.000095637994662983496
train_batch_size: 16
eval_batch_size: 16
seed: 13
gradient_accumulation_steps: 16
total_train_batch_size: 316
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_steps: 500
num_epochs: 100
mixed_precision_training: Native AMP


### Training results


Step	Training Loss	Validation Loss	Wer
500	4.825900	1.001413	0.810308
1000	0.561400	0.202275	0.361987
1500	0.298900	0.169643	0.326449
2000	0.236500	0.168602	0.316215
2500	0.199100	0.182484	0.308587
3000	0.179100	0.178076	0.303005
3500	0.161500	0.179107	0.299935
4000	0.151700	0.183371	0.295283
4500	0.143700	0.184443	0.295283
5000	0.138900	0.184265	0.292771

### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.10.3

#### Evaluation Commands

1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test`

```bash
python eval.py --model_id Akashpb13/xlsr_hungarian_new --dataset mozilla-foundation/common_voice_7_0 --config hu --split test
```