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clasificador-emotion-bert – AI Model by yolandadiaz23 | AlphaNeural AI
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clasificador-emotion-bert
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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clasificador-emotion-bert
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: 0.2305
Accuracy: 0.9285
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
0.2680
1.0
2000
0.2133
0.926
0.1464
2.0
4000
0.1666
0.933
0.1068
3.0
6000
0.2305
0.9285
Framework versions
Transformers 5.7.0
Pytorch 2.10.0+cu128
Datasets 4.8.5
Tokenizers 0.22.2
