This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MYV dataset. It achieves the following results on the evaluation set:

Loss: 1.0356
Wer: 0.6524

Evaluation Commands

1. To evaluate on mozilla-foundation/common_voice_8_0 with test split

python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-myv-a1 --dataset mozilla-foundation/common_voice_8_0 --config myv --split test --log_outputs

2. To evaluate on speech-recognition-community-v2/dev_data

Erzya language not found in speech-recognition-community-v2/dev_data

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0004
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 800
num_epochs: 200.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.649	9.62	500	3.0038	1.0
1.6272	19.23	1000	0.7362	0.7819
1.1354	28.85	1500	0.6410	0.7111
1.0424	38.46	2000	0.6907	0.7431
0.9293	48.08	2500	0.7249	0.7102
0.8246	57.69	3000	0.7422	0.6966
0.7837	67.31	3500	0.7413	0.6813
0.7147	76.92	4000	0.7873	0.6930
0.6276	86.54	4500	0.8038	0.6677
0.6041	96.15	5000	0.8240	0.6831
0.5336	105.77	5500	0.8748	0.6749
0.4705	115.38	6000	0.9006	0.6497
0.43	125.0	6500	0.8954	0.6551
0.3859	134.62	7000	0.9074	0.6614
0.3342	144.23	7500	0.9693	0.6560
0.3155	153.85	8000	1.0073	0.6691
0.2673	163.46	8500	1.0170	0.6632
0.2409	173.08	9000	1.0304	0.6709
0.2189	182.69	9500	0.9965	0.6546
0.1973	192.31	10000	1.0360	0.6551

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.2+cu102
Datasets 1.18.2.dev0
Tokenizers 0.11.0

Evaluation Command

!python eval.py
--model_id DrishtiSharma/wav2vec2-large-xls-r-300m-myv-v1
--dataset mozilla-foundation/common_voice_8_0 --config myv --split test --log_outputs