This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - ES dataset. It achieves the following results on the evaluation set:

Loss: 0.1461
Wer: 1.0063

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: 7.5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
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: 2000
num_epochs: 5.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.953	0.15	1000	2.9528	1.0
1.1519	0.3	2000	0.3735	1.0357
1.0278	0.45	3000	0.2529	1.0390
0.9922	0.61	4000	0.2208	1.0270
0.9618	0.76	5000	0.2088	1.0294
0.9364	0.91	6000	0.2019	1.0214
0.9179	1.06	7000	0.1940	1.0294
0.9154	1.21	8000	0.1915	1.0290
0.8985	1.36	9000	0.1837	1.0211
0.9055	1.51	10000	0.1838	1.0273
0.8861	1.67	11000	0.1765	1.0139
0.892	1.82	12000	0.1723	1.0188
0.8778	1.97	13000	0.1735	1.0092
0.8645	2.12	14000	0.1707	1.0106
0.8595	2.27	15000	0.1713	1.0186
0.8392	2.42	16000	0.1686	1.0053
0.8436	2.57	17000	0.1653	1.0096
0.8405	2.73	18000	0.1689	1.0077
0.8382	2.88	19000	0.1645	1.0114
0.8247	3.03	20000	0.1647	1.0078
0.8219	3.18	21000	0.1611	1.0026
0.8024	3.33	22000	0.1580	1.0062
0.8087	3.48	23000	0.1578	1.0038
0.8097	3.63	24000	0.1556	1.0057
0.8094	3.79	25000	0.1552	1.0035
0.7836	3.94	26000	0.1516	1.0052
0.8042	4.09	27000	0.1515	1.0054
0.7925	4.24	28000	0.1499	1.0031
0.7855	4.39	29000	0.1490	1.0041
0.7814	4.54	30000	0.1482	1.0068
0.7859	4.69	31000	0.1460	1.0066
0.7819	4.85	32000	0.1464	1.0062
0.7784	5.0	33000	0.1460	1.0063

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.2+cu102
Datasets 1.18.3.dev0
Tokenizers 0.11.0

pablouribe/xls-r-spanish-test

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

pablouribe/
xls-r-spanish-test