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---
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- mr
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-large-xls-r-300m-mr-v2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: mr
metrics:
- name: Test WER
type: wer
value: 0.49378259125551544
- name: Test CER
type: cer
value: 0.12470799640610962
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: mr
metrics:
- name: Test WER
type: wer
value: NA
- name: Test CER
type: cer
value: NA
---
<!-- 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. -->
# wav2vec2-large-xls-r-300m-mr-v2
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: 0.8729
- Wer: 0.4942
### Evaluation Commands
1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 --dataset mozilla-foundation/common_voice_8_0 --config mr --split test --log_outputs
2. To evaluate on speech-recognition-community-v2/dev_data
python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-mr-v2 --dataset speech-recognition-community-v2/dev_data --config mr --split validation --chunk_length_s 10 --stride_length_s 1
Note: Marathi language not found in speech-recognition-community-v2/dev_data!
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.000333
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 8.4934 | 9.09 | 200 | 3.7326 | 1.0 |
| 3.4234 | 18.18 | 400 | 3.3383 | 0.9996 |
| 3.2628 | 27.27 | 600 | 2.7482 | 0.9992 |
| 1.7743 | 36.36 | 800 | 0.6755 | 0.6787 |
| 1.0346 | 45.45 | 1000 | 0.6067 | 0.6193 |
| 0.8137 | 54.55 | 1200 | 0.6228 | 0.5612 |
| 0.6637 | 63.64 | 1400 | 0.5976 | 0.5495 |
| 0.5563 | 72.73 | 1600 | 0.7009 | 0.5383 |
| 0.4844 | 81.82 | 1800 | 0.6662 | 0.5287 |
| 0.4057 | 90.91 | 2000 | 0.6911 | 0.5303 |
| 0.3582 | 100.0 | 2200 | 0.7207 | 0.5327 |
| 0.3163 | 109.09 | 2400 | 0.7107 | 0.5118 |
| 0.2761 | 118.18 | 2600 | 0.7538 | 0.5118 |
| 0.2415 | 127.27 | 2800 | 0.7850 | 0.5178 |
| 0.2127 | 136.36 | 3000 | 0.8016 | 0.5034 |
| 0.1873 | 145.45 | 3200 | 0.8302 | 0.5187 |
| 0.1723 | 154.55 | 3400 | 0.9085 | 0.5223 |
| 0.1498 | 163.64 | 3600 | 0.8396 | 0.5126 |
| 0.1425 | 172.73 | 3800 | 0.8776 | 0.5094 |
| 0.1258 | 181.82 | 4000 | 0.8651 | 0.5014 |
| 0.117 | 190.91 | 4200 | 0.8772 | 0.4970 |
| 0.1093 | 200.0 | 4400 | 0.8729 | 0.4942 |
### Framework versions
- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0
|