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bertweet-olid – AI Model by ARC4N3 | AlphaNeural AI
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ARC4N3
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bertweet-olid
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
finiteautomata/bertweet-base-sentiment-analysis
finetune
autotrain_compatible
endpoints_compatible
us
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bertweet-olid
This model is a fine-tuned version of
finiteautomata/bertweet-base-sentiment-analysis
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.0303
Accuracy: 0.8104
F1: 0.8082
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.3675
1.0
774
0.4257
0.8233
0.8217
0.3006
2.0
1548
0.3651
0.8385
0.8383
0.2461
3.0
2322
0.4812
0.8301
0.8298
0.202
4.0
3096
0.6835
0.8324
0.8324
0.1533
5.0
3870
1.0303
0.8104
0.8082
Framework versions
Transformers 4.38.1
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2
