This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GTTSEHU/BASQUE_PARLIAMENT_1 - NA dataset. It achieves the following results on the evaluation set:

Loss: 0.0846
Wer: 0.0367
Cer: 0.0132

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: 0.0001
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 32
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 6.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.7054	0.19	4000	0.1011	0.0871	0.0227
0.0856	0.39	8000	0.0995	0.0747	0.0207
0.075	0.58	12000	0.0868	0.0647	0.0185
0.0694	0.77	16000	0.0853	0.0619	0.0183
0.0658	0.97	20000	0.0778	0.0573	0.0171
0.0589	1.16	24000	0.0821	0.0546	0.0166
0.0572	1.35	28000	0.0827	0.0558	0.0170
0.0551	1.55	32000	0.0830	0.0533	0.0169
0.054	1.74	36000	0.0788	0.0512	0.0162
0.0524	1.93	40000	0.0783	0.0489	0.0156
0.048	2.13	44000	0.0861	0.0492	0.0160
0.046	2.32	48000	0.0763	0.0494	0.0154
0.0456	2.51	52000	0.0835	0.0471	0.0153
0.0439	2.71	56000	0.0790	0.0469	0.0152
0.0436	2.9	60000	0.0832	0.0472	0.0155
0.0406	3.09	64000	0.0810	0.0442	0.0148
0.0386	3.29	68000	0.0810	0.0436	0.0146
0.038	3.48	72000	0.0778	0.0430	0.0143
0.0373	3.67	76000	0.0785	0.0430	0.0144
0.0363	3.87	80000	0.0788	0.0421	0.0144
0.0348	4.06	84000	0.0823	0.0423	0.0144
0.0323	4.25	88000	0.0819	0.0407	0.0143
0.0319	4.45	92000	0.0809	0.0410	0.0142
0.0314	4.64	96000	0.0821	0.0400	0.0138
0.0306	4.83	100000	0.0813	0.0389	0.0137
0.0295	5.03	104000	0.0820	0.0377	0.0131
0.0275	5.22	108000	0.0866	0.0378	0.0137
0.0267	5.41	112000	0.0831	0.0376	0.0134
0.0264	5.61	116000	0.0845	0.0369	0.0132
0.0258	5.8	120000	0.0859	0.0370	0.0133
0.0254	6.0	124000	0.0846	0.0367	0.0132

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.1+cu121
Datasets 2.15.1.dev0
Tokenizers 0.15.0

gttsehu/wav2vec2-xls-r-300m-bp1-es_eu

facebook/wav2vec2-xls-r-300m

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gttsehu/
wav2vec2-xls-r-300m-bp1-es_eu