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HW_DL_10_Competitions_v2 – AI Model by kirilica | AlphaNeural AI
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HW_DL_10_Competitions_v2
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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HW_DL_10_Competitions_v2
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.9199
F1: 0.6244
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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use 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: 4
Training results
Training Loss
Epoch
Step
Validation Loss
F1
1.0697
1.0
563
1.0279
0.5366
0.8777
2.0
1126
0.9148
0.6086
0.7762
3.0
1689
0.8739
0.6292
0.6937
4.0
2252
0.9199
0.6244
Framework versions
Transformers 4.47.0
Pytorch 2.4.0
Datasets 3.1.0
Tokenizers 0.21.0
