wav2vec2-bloom-speech-fra

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Model description

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the SIL-AI/bloom-speech - FRA dataset. It achieves the following results on the evaluation set:

Users should refer to the original model for tutorials on using a trained model for inference.

Users of this model must abide by the SIL RAIL-M License.

This model is created as a proof of concept and no guarantees are made regarding the performance of the model is specific situations.

Training, Validation, and Test datasets were generated from the same corpus, ensuring that no duplicate files were used.

Standard finetuning of XLS-R was used based on the examples in the Hugging Face Transformers Github

The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
No log	41.62	250	1.0210	0.7260	0.2412
2.4099	83.31	500	0.8338	0.4774	0.1514
2.4099	124.92	750	0.8023	0.4138	0.1205
0.0364	166.62	1000	0.7624	0.4068	0.1261
0.0364	208.31	1250	0.8166	0.3644	0.1149
0.0226	249.92	1500	0.8175	0.3686	0.1202
0.0226	291.62	1750	0.9210	0.3715	0.1170
0.0143	333.31	2000	0.8273	0.3729	0.1175
0.0143	374.92	2250	0.8743	0.3418	0.1109
0.0093	416.62	2500	0.8424	0.3432	0.1165
0.0093	458.31	2750	0.8365	0.3333	0.1053
0.0064	499.92	3000	0.9097	0.3432	0.1111
0.0064	541.62	3250	0.9744	0.3404	0.1098
0.0041	583.31	3500	0.9257	0.3489	0.1079
0.0041	624.92	3750	0.9047	0.3220	0.1031
0.0026	666.62	4000	0.8852	0.3263	0.1026
0.0026	708.31	4250	0.9000	0.3249	0.0986
0.0016	749.92	4500	0.9389	0.3376	0.1005
0.0016	791.62	4750	0.9329	0.3079	0.0970
0.0017	833.31	5000	0.9322	0.3164	0.0991
0.0017	874.92	5250	0.9351	0.3079	0.0991
0.0008	916.62	5500	0.9346	0.3051	0.0978
0.0008	958.31	5750	0.9391	0.3093	0.0991
0.0007	999.92	6000	0.9435	0.3065	0.0978