xtreme_s_xlsr_300m_fleurs_asr

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Cer	Validation Loss	Wer
4.677	0.13	1000	1.0	3.2323	1.0
4.1512	0.26	2000	0.5098	1.7858	0.9869
1.119	0.39	3000	0.4412	1.6628	0.9063
0.8573	0.52	4000	0.3588	1.3440	0.9016
1.0232	0.65	5000	0.3690	1.3004	0.8775
0.6328	0.78	6000	0.3354	1.2219	0.8331
0.6636	0.91	7000	0.3604	1.2839	0.8637
0.6536	1.04	8000	0.3420	1.2481	0.8504
0.5002	1.17	9000	0.3518	1.2514	0.8403
0.4785	1.3	10000	0.3399	1.2409	0.8570
0.517	1.43	11000	0.3599	1.3058	0.8654
0.506	1.56	12000	0.3484	1.2350	0.8441
0.4013	1.69	13000	0.3327	1.1982	0.8246
0.3521	1.82	14000	0.3270	1.1653	0.8265
0.4265	1.95	15000	0.3562	1.2647	0.8564
0.3949	2.08	16000	0.3490	1.2988	0.8480
0.3059	2.21	17000	0.3327	1.2332	0.8323
0.3618	2.34	18000	0.3480	1.2394	0.8517
0.2567	2.47	19000	0.3365	1.2294	0.8394
0.3501	2.6	20000	0.3271	1.1853	0.8250
0.2766	2.73	21000	0.3425	1.2339	0.8443
0.3396	2.86	22000	0.3501	1.2768	0.8669
0.3566	2.99	23000	0.3477	1.2648	0.8710
0.3166	3.12	24000	0.3550	1.3773	0.8641
0.2388	3.25	25000	0.3301	1.2374	0.8316
0.2057	3.38	26000	0.3429	1.2846	0.8560
0.2264	3.51	27000	0.3469	1.2676	0.8542
0.1998	3.64	28000	0.3531	1.3365	0.8655
0.2701	3.77	29000	0.3518	1.3124	0.8711
0.18	3.9	30000	0.3498	1.3095	0.8648
0.1337	4.03	31000	0.3397	1.2941	0.8452
0.162	4.16	32000	0.3320	1.2942	0.8295
0.2776	4.29	33000	0.3275	1.2690	0.8276
0.1634	4.42	34000	0.3307	1.3145	0.8331
0.2172	4.54	35000	0.3334	1.3031	0.8435
0.1305	4.67	36000	0.3303	1.2768	0.8321
0.1436	4.8	37000	0.3353	1.2968	0.8416
0.134	4.93	38000	0.3330	1.2864	0.8344