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---
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-mr
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
type: mozilla-foundation/common_voice_8_0
name: Common Voice 8
args: mr
metrics:
- type: wer # Required. Example: wer
value: 31.57 # Required. Example: 20.90
name: Test WER # Optional. Example: Test WER
- name: Test CER
type: cer
value: 6.93
---
<!-- 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_8_0 - MR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.494580
- Wer: 0.395909
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 200.0
- mixed_precision_training: Native AMP
### Training results
| Step | Training Loss | Validation Loss | Wer |
|---|---|---|---|
| 400 | 3.794000 | 3.532227 | 1.000000 |
| 800 | 3.362400 | 3.359044 | 1.000000 |
| 1200 | 2.293900 | 1.011279 | 0.829924 |
| 1600 | 1.233000 | 0.502743 | 0.593662 |
| 2000 | 0.962600 | 0.412519 | 0.496992 |
| 2400 | 0.831800 | 0.402903 | 0.493783 |
| 2800 | 0.737000 | 0.389773 | 0.469314 |
| 3200 | 0.677100 | 0.373987 | 0.436021 |
| 3600 | 0.634400 | 0.383823 | 0.432010 |
| 4000 | 0.586000 | 0.375610 | 0.419575 |
| 4400 | 0.561000 | 0.387891 | 0.418371 |
| 4800 | 0.518500 | 0.386357 | 0.417569 |
| 5200 | 0.515300 | 0.415069 | 0.430004 |
| 5600 | 0.478100 | 0.399211 | 0.408744 |
| 6000 | 0.468100 | 0.424542 | 0.402327 |
| 6400 | 0.439400 | 0.430979 | 0.410750 |
| 6800 | 0.429600 | 0.427700 | 0.409146 |
| 7200 | 0.400300 | 0.451111 | 0.419976 |
| 7600 | 0.395100 | 0.463446 | 0.405134 |
| 8000 | 0.381800 | 0.454752 | 0.407942 |
| 8400 | 0.371500 | 0.461547 | 0.404733 |
| 8800 | 0.362500 | 0.461543 | 0.411151 |
| 9200 | 0.338200 | 0.468299 | 0.417168 |
| 9600 | 0.338800 | 0.480989 | 0.412355 |
| 10000 | 0.317600 | 0.475700 | 0.410750 |
| 10400 | 0.315100 | 0.478920 | 0.403530 |
| 10800 | 0.296200 | 0.480600 | 0.398315 |
| 11200 | 0.299000 | 0.477083 | 0.393502 |
| 11600 | 0.290000 | 0.465646 | 0.393903 |
| 12000 | 0.290900 | 0.490041 | 0.405937 |
| 12400 | 0.275600 | 0.489354 | 0.399519 |
| 12800 | 0.272600 | 0.494580 | 0.395909 |
| 13200 | 0.265900 | 0.497918 | 0.397112 |
| 13600 | 0.266300 | 0.498627 | 0.397513 |
| 14000 | 0.259600 | 0.504610 | 0.401524 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.3.dev0
- Tokenizers 0.11.0
### Eval results on Common Voice 8 "test" (WER):
| Without LM | With LM |
|---|---|
| 40.513437625350984 | 31.56839149618933 |
|