finetuning-sentiment-model-3000-samples_4 – AI Model by mamledes | AlphaNeural AI

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mamledes/
finetuning-sentiment-model-3000-samples_4

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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finetuning-sentiment-model-3000-samples_4

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: 0.5182
Accuracy: 0.8125
F1: 0.6667

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: 3
eval_batch_size: 3
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	14	0.5887	0.6875	0.5455
No log	2.0	28	0.5182	0.8125	0.6667
No log	3.0	42	0.5767	0.75	0.6
No log	4.0	56	0.7271	0.6875	0.5455
No log	5.0	70	0.7011	0.75	0.6
No log	6.0	84	0.6895	0.75	0.6

Framework versions

Transformers 4.43.3
Pytorch 2.4.0
Datasets 2.19.1
Tokenizers 0.19.1