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

Loss: 0.8318
Wer: 0.5174

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: 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_ratio: 0.12
num_epochs: 120

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.882	25.0	400	1.2290	0.8182
0.8275	50.0	800	0.6835	0.5398
0.337	75.0	1200	0.7789	0.5107
0.2113	100.0	1600	0.8318	0.5174

Framework versions

Transformers 4.16.2
Pytorch 1.10.1+cu102
Datasets 1.17.1.dev0
Tokenizers 0.10.3

Test Evaluation

Common Voice Assamese Test Set (v7.0)

WER: 0.7224
CER: 0.2882

reichenbach/wav2vec2-large-xls-r-300m-as

wav2vec2-large-xls-r-300m-as

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Test Evaluation

reichenbach/
wav2vec2-large-xls-r-300m-as