metadata

language:
  - eo
license: apache-2.0
tags:
  - automatic-speech-recognition
  - robust-speech-event
  - common_voice
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: wav2vec2-xls-r-300m-eo
    results: []

wav2vec2-xls-r-300m-eo

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

Loss: 0.2584
Wer: 0.3114

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.1701	0.8	500	2.8105	1.0
1.9143	1.6	1000	0.5977	0.7002
1.1259	2.4	1500	0.5063	0.6157
0.9732	3.2	2000	0.4264	0.5673
0.8983	4.0	2500	0.4249	0.4902
0.8507	4.8	3000	0.3811	0.4536
0.8064	5.6	3500	0.3643	0.4467
0.7866	6.4	4000	0.3600	0.4453
0.7773	7.2	4500	0.3724	0.4470
0.747	8.0	5000	0.3501	0.4189
0.7279	8.8	5500	0.3500	0.4261
0.7153	9.6	6000	0.3328	0.3966
0.7	10.4	6500	0.3314	0.3869
0.6784	11.2	7000	0.3396	0.4051
0.6582	12.0	7500	0.3236	0.3899
0.6478	12.8	8000	0.3263	0.3832
0.6277	13.6	8500	0.3139	0.3769
0.6053	14.4	9000	0.2955	0.3536
0.5777	15.2	9500	0.2793	0.3413
0.5631	16.0	10000	0.2789	0.3353
0.5446	16.8	10500	0.2709	0.3264
0.528	17.6	11000	0.2693	0.3234
0.5169	18.4	11500	0.2656	0.3193
0.5041	19.2	12000	0.2575	0.3102
0.4971	20.0	12500	0.2584	0.3114

Framework versions

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