This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.2704
Wer: 0.2306

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: 5e-05
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_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.283	0.7979	300	0.3271	0.3871
0.2931	1.5957	600	0.2957	0.3468
0.2358	2.3936	900	0.2746	0.3299
0.1842	3.1915	1200	0.2473	0.2846
0.1532	3.9894	1500	0.2257	0.2632
0.1198	4.7872	1800	0.2403	0.2600
0.1027	5.5851	2100	0.2239	0.2513
0.0837	6.3830	2400	0.2310	0.2591
0.0678	7.1809	2700	0.2295	0.2402
0.0527	7.9787	3000	0.2428	0.2334
0.0374	8.7766	3300	0.2448	0.2347
0.0298	9.5745	3600	0.2704	0.2306

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu118
Datasets 2.19.2
Tokenizers 0.19.1

roshna-omer/w2v-bert-2.0-krd-colab-CV16.0

w2v-bert-2.0-krd-colab-CV16.0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

roshna-omer/
w2v-bert-2.0-krd-colab-CV16.0