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deberta-disaster-tweet-recognizer – AI Model by onegoodlad | AlphaNeural AI
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deberta-disaster-tweet-recognizer
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transformers
safetensors
deberta-v2
text-classification
generated_from_trainer
microsoft/deberta-v3-large
finetune
mit
autotrain_compatible
endpoints_compatible
us
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Deberta Disaster Tweet Recognizer
This model is a fine-tuned version of
microsoft/deberta-v3-large
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4104
F1: 0.8
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: 8e-06
train_batch_size: 32
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1
No log
1.0
191
0.4159
0.7894
No log
2.0
382
0.3845
0.7973
0.4497
3.0
573
0.3952
0.8016
0.4497
4.0
764
0.4104
0.8
Framework versions
Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2
