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finetuning-sentiment-model-3000-samples – AI Model by MPDLCK | AlphaNeural AI
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finetuning-sentiment-model-3000-samples
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tensorboard
safetensors
distilbert
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
us
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finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.4796
eval_accuracy: 0.8833
eval_f1: 0.8860
eval_runtime: 10.2483
eval_samples_per_second: 29.273
eval_steps_per_second: 1.854
step: 0
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: 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: 2
Framework versions
Transformers 4.37.2
Pytorch 2.11.0+cu128
Datasets 2.16.1
Tokenizers 0.15.2
