my_awesome_asr_mind_model

This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset. It achieves the following results on the evaluation set:

• Loss: 3.0295
• Wer: 1.0

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: 1e-05
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
36.0013	0.71	50	54.8783	1.0231
29.2024	1.43	100	43.3910	1.0
18.6027	2.14	150	24.3702	1.0
6.5918	2.86	200	7.0226	1.0
4.0512	3.57	250	4.3558	1.0
3.6216	4.29	300	4.0701	1.0
3.4344	5.0	350	3.8139	1.0
3.5985	5.71	400	3.6550	1.0
3.5004	6.43	450	3.5076	1.0
3.3916	7.14	500	3.4591	1.0
3.1966	7.86	550	3.3332	1.0
3.2384	8.57	600	3.2828	1.0
3.1981	9.29	650	3.2563	1.0
3.1743	10.0	700	3.2011	1.0
3.1251	10.71	750	3.1600	1.0
3.0371	11.43	800	3.1436	1.0
3.0702	12.14	850	3.1633	1.0
3.0748	12.86	900	3.1194	1.0
3.0459	13.57	950	3.1797	1.0
3.0496	14.29	1000	3.1073	1.0
3.0744	15.0	1050	3.1033	1.0
3.0342	15.71	1100	3.0702	1.0
3.0469	16.43	1150	3.0680	1.0
3.0234	17.14	1200	3.0650	1.0
3.0739	17.86	1250	3.0586	1.0
2.9964	18.57	1300	3.0542	1.0
3.0906	19.29	1350	3.0519	1.0
2.9823	20.0	1400	3.0456	1.0
3.038	20.71	1450	3.0399	1.0
2.9952	21.43	1500	3.0357	1.0
3.0092	22.14	1550	3.0571	1.0
2.9838	22.86	1600	3.0354	1.0
3.0611	23.57	1650	3.0435	1.0
2.9924	24.29	1700	3.0368	1.0
2.9854	25.0	1750	3.0580	1.0
3.0193	25.71	1800	3.0347	1.0
2.9694	26.43	1850	3.0335	1.0
3.0039	27.14	1900	3.0318	1.0
2.9789	27.86	1950	3.0322	1.0
2.9828	28.57	2000	3.0295	1.0

Framework versions

• Transformers 4.30.0
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.13.3