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Chituyi/
wav2vec2-swahili-xlsr-sw300m-asr

Name: wav2vec2-swahili-xlsr-sw300m-asr
Availability: InStock

automatic-speech-recognition

generated_from_trainer

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wav2vec2-large-xls-r-300m-tr-colab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_8_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.4900
Wer: 0.97

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
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
6.5497	0.4	50	2.9819	1.0
2.8809	0.8	100	2.8873	1.0
2.8416	1.2	150	2.8427	1.0
2.8145	1.6	200	2.8067	1.0
2.747	2.0	250	2.7092	1.0
2.1095	2.4	300	1.3472	1.0
0.9546	2.8	350	0.7708	0.9975
0.6104	3.2	400	0.6317	0.9825
0.4941	3.6	450	0.5427	0.97
0.4345	4.0	500	0.5314	0.975
0.3327	4.4	550	0.4927	0.9625
0.3099	4.8	600	0.4900	0.97

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2

Chituyi/wav2vec2-swahili-xlsr-sw300m-asr

wav2vec2-large-xls-r-300m-tr-colab

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Chituyi/
wav2vec2-swahili-xlsr-sw300m-asr