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pcm-mbert-focal – AI Model by jaycentg | AlphaNeural AI
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pcm-mbert-focal
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-multilingual-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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pcm-mbert-focal
This model is a fine-tuned version of
google-bert/bert-base-multilingual-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 19.7314
F1-micro: 0.4954
F1-macro: 0.4661
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: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 37
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
F1-micro
F1-macro
151.7218
1.0
94
20.5053
0.4192
0.4039
142.0258
2.0
188
19.6631
0.4415
0.4189
135.1295
3.0
282
19.4821
0.4821
0.4633
129.6306
4.0
376
19.7314
0.4954
0.4661
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1
