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NiGuLa/
google-bert_bert-base-multilingual-cased_ep10_lr0.0001_batchpergpu16_gpu1_weighted

Name: google-bert_bert-base-multilingual-cased_ep10_lr0.0001_batchpergpu16_gpu1_weighted
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google-bert_bert-base-multilingual-cased_ep10_lr0.0001_batchpergpu16_gpu1_weighted

This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	F1 Micro	F1 Macro	Exact Match
0.4412	0.9924	131	0.5074	0.0	0.0	0.4943
0.5288	1.9848	262	0.4785	0.0	0.0	0.4943
0.5164	2.9773	393	0.4923	0.5170	0.0984	0.3258
0.5543	3.9697	524	0.4909	0.0	0.0	0.4943
0.4382	4.9621	655	0.5024	0.0	0.0	0.4943