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---
language:
- et
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- robust-speech-event
- et
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: ''
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: et
metrics:
- name: Test WER
type: wer
value: 0.34753420299077314
- name: Test CER
type: cer
value: 0.07542956089330906
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: et
metrics:
- name: Test WER
type: wer
value: 47.17
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: et
metrics:
- name: Test WER
type: wer
value: 54.72
---
<!-- 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. -->
#
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 - ET dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4835
- Wer: 0.3475
## 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: 72
- eval_batch_size: 72
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 144
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3825 | 12.5 | 500 | 0.4022 | 0.5059 |
| 0.1592 | 25.0 | 1000 | 0.4585 | 0.4456 |
| 0.1215 | 37.5 | 1500 | 0.4550 | 0.4164 |
| 0.0972 | 50.0 | 2000 | 0.4725 | 0.4088 |
| 0.0731 | 62.5 | 2500 | 0.4568 | 0.3824 |
| 0.0527 | 75.0 | 3000 | 0.4712 | 0.3653 |
| 0.0428 | 87.5 | 3500 | 0.4813 | 0.3520 |
| 0.0383 | 100.0 | 4000 | 0.4835 | 0.3475 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.4.dev0
- Tokenizers 0.11.0
|