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---
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
```
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