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clasificator-tweet-sentiment – AI Model by KaraSpdrnr | AlphaNeural AI
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clasificator-tweet-sentiment
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transformers
safetensors
bert
text-classification
classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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clasificator-tweet-sentiment
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.4390
Accuracy: 0.6774
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: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6407
1.0
5702
0.6941
0.6876
0.4589
2.0
11404
0.8406
0.6699
0.2564
3.0
17106
1.4390
0.6774
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2
