anton-l/xtreme_s_xlsr_300m_minds14

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xtremesxlsr300mminds14

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME_S - MINDS14.ALL dataset. It achieves the following results on the evaluation set:

• —Accuracy: 0.9033
• —Accuracy Cs-cz: 0.9164
• —Accuracy De-de: 0.9477
• —Accuracy En-au: 0.9235
• —Accuracy En-gb: 0.9324
• —Accuracy En-us: 0.9326
• —Accuracy Es-es: 0.9177
• —Accuracy Fr-fr: 0.9444
• —Accuracy It-it: 0.9167
• —Accuracy Ko-kr: 0.8649
• —Accuracy Nl-nl: 0.9450
• —Accuracy Pl-pl: 0.9146
• —Accuracy Pt-pt: 0.8940
• —Accuracy Ru-ru: 0.8667
• —Accuracy Zh-cn: 0.7291
• —F1: 0.9015
• —F1 Cs-cz: 0.9154
• —F1 De-de: 0.9467
• —F1 En-au: 0.9199
• —F1 En-gb: 0.9334
• —F1 En-us: 0.9308
• —F1 Es-es: 0.9158
• —F1 Fr-fr: 0.9436
• —F1 It-it: 0.9135
• —F1 Ko-kr: 0.8642
• —F1 Nl-nl: 0.9440
• —F1 Pl-pl: 0.9159
• —F1 Pt-pt: 0.8883
• —F1 Ru-ru: 0.8646
• —F1 Zh-cn: 0.7249
• —Loss: 0.4119
• —Loss Cs-cz: 0.3790
• —Loss De-de: 0.2649
• —Loss En-au: 0.3459
• —Loss En-gb: 0.2853
• —Loss En-us: 0.2203
• —Loss Es-es: 0.2731
• —Loss Fr-fr: 0.1909
• —Loss It-it: 0.3520
• —Loss Ko-kr: 0.5431
• —Loss Nl-nl: 0.2515
• —Loss Pl-pl: 0.4113
• —Loss Pt-pt: 0.4798
• —Loss Ru-ru: 0.6470
• —Loss Zh-cn: 1.1216
• —Predict Samples: 4086

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: 0.0003
• —trainbatchsize: 32
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 2
• —totaltrainbatch_size: 64
• —totalevalbatch_size: 16
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 1500
• —num_epochs: 50.0
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.18.0.dev0
• —Pytorch 1.10.2+cu113
• —Datasets 2.0.1.dev0
• —Tokenizers 0.11.6