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f1_score_model – AI Model by bellge | AlphaNeural AI
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f1_score_model
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-large
finetune
mit
autotrain_compatible
endpoints_compatible
us
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f1_score_model
This model is a fine-tuned version of
roberta-large
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6087
Accuracy: 0.7016
F1: 0.6217
Precision: 0.5813
Recall: 0.7016
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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.4236
4.98
1000
0.6087
0.7016
0.6217
0.5813
0.7016
Framework versions
Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2
