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finetuning-sentiment-model – AI Model by karina-aquino | AlphaNeural AI
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finetuning-sentiment-model
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transformers
pytorch
distilbert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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finetuning-sentiment-model
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2295
Accuracy: 0.9311
F1: 0.9261
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.2477
1.0
1316
0.2295
0.9311
0.9261
Framework versions
Transformers 4.30.1
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3