---
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
"facebook/wav2vec2-xls-r-300m" was finetuned.

## Intended uses & limitations
More information needed
## Training and evaluation data
Training data - 
Common voice hungarian train.tsv, dev.tsv, invalidated.tsv, reported.tsv, other.tsv and validated.tsv
Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0

## Training procedure
For creating the train dataset, all possible datasets were appended and 90-10 split was used. 

### 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
```