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Niger-Malitamasheq-finetuned – AI Model by YassineBenlaria | AlphaNeural AI
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YassineBenlaria
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Niger-Malitamasheq-finetuned
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transformers
pytorch
wav2vec2
automatic-speech-recognition
generated_from_trainer
LIA-AvignonUniversity/IWSLT2022-Niger-Mali
finetune
endpoints_compatible
us
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Niger-Malitamasheq-finetuned
This model is a fine-tuned version of
LIA-AvignonUniversity/IWSLT2022-Niger-Mali
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.9747
Cer: 0.9979
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: 3e-05
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: 60
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
8.7075
8.57
30
5.0922
0.9979
4.4557
17.14
60
3.3251
0.9979
3.5394
25.71
90
3.1326
0.9979
3.2067
34.29
120
3.0365
0.9979
3.0958
42.86
150
2.9906
0.9979
3.0147
51.43
180
2.9747
0.9979
Framework versions
Transformers 4.32.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3
