DrishtiSharma/wav2vec2-xls-r-300m-rm-vallader-d1

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

• Loss: 0.2754
• Wer: 0.2831

Evaluation Commands

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

python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-300m-rm-vallader-d1 --dataset mozilla-foundation/common_voice_8_0 --config rm-vallader --split test --log_outputs

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

Romansh-Vallader language not found in speech-recognition-community-v2/dev_data

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 7.5e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 100.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.927	15.15	500	2.9196	1.0
1.3835	30.3	1000	0.5879	0.5866
0.7415	45.45	1500	0.3077	0.3316
0.5575	60.61	2000	0.2735	0.2954
0.4581	75.76	2500	0.2707	0.2802
0.3977	90.91	3000	0.2785	0.2809

Framework versions

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