wav2vec2-base-common-voice-40p-persian-colab

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.1805
• Wer: 0.6024

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: 0.00018
• 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
• lr_scheduler_warmup_steps: 2000
• num_epochs: 40
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.9643	1.05	200	3.0107	1.0
2.7552	2.11	400	2.7370	0.9997
1.9144	3.16	600	1.8266	0.9703
1.502	4.21	800	1.3981	0.8996
1.3155	5.26	1000	1.2148	0.8507
0.9471	6.32	1200	1.1698	0.7860
0.8391	7.37	1400	1.1106	0.7857
0.7986	8.42	1600	1.1858	0.7769
0.7692	9.47	1800	1.1227	0.7603
0.7871	10.53	2000	1.0626	0.7612
0.6795	11.58	2200	1.1249	0.7209
0.4842	12.63	2400	1.1626	0.7336
0.492	13.68	2600	1.0995	0.7212
0.5117	14.74	2800	1.1406	0.7105
0.5649	15.79	3000	1.0603	0.6819
0.3232	16.84	3200	1.1781	0.7070
0.4098	17.89	3400	1.1182	0.6764
0.3917	18.95	3600	1.1320	0.6750
0.3712	20.0	3800	1.1920	0.6724
0.3157	21.05	4000	1.1102	0.6786
0.2397	22.11	4200	1.1924	0.6519
0.2751	23.16	4400	1.1497	0.6468
0.2279	24.21	4600	1.2274	0.6400
0.393	25.26	4800	1.1741	0.6436
0.1748	26.32	5000	1.2038	0.6327
0.1727	27.37	5200	1.1639	0.6347
0.255	28.42	5400	1.1948	0.6367
0.2261	29.47	5600	1.1560	0.6362
0.2359	30.53	5800	1.1227	0.6269
0.1668	31.58	6000	1.1861	0.6295
0.1699	32.63	6200	1.2442	0.6314
0.14	33.68	6400	1.1340	0.6277
0.1919	34.74	6600	1.1691	0.6139
0.2527	35.79	6800	1.1511	0.6110
0.1219	36.84	7000	1.2062	0.6139
0.1389	37.89	7200	1.2142	0.6072
0.135	38.95	7400	1.1967	0.6040
0.1563	40.0	7600	1.1805	0.6024

Framework versions

• Transformers 4.11.3
• Pytorch 1.10.0+cu113
• Datasets 1.18.3
• Tokenizers 0.10.3