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anjan-k/
Sentiment-Analysis-FineTune-HuggingFace

Name: Sentiment-Analysis-FineTune-HuggingFace
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

finetune

apache-2.0

text-embeddings-inference

endpoints_compatible

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Sentiment-Analysis-FineTune-HuggingFace

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8521
Accuracy: 0.7529
F1: 0.7516

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6061	1.0	1952	0.5761	0.7616	0.7620
0.4957	2.0	3904	0.5936	0.7589	0.7603
0.382	3.0	5856	0.6639	0.7535	0.7543
0.2679	4.0	7808	0.8521	0.7529	0.7516

Framework versions

Transformers 4.55.0
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.4

anjan-k/Sentiment-Analysis-FineTune-HuggingFace

Sentiment-Analysis-FineTune-HuggingFace

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

anjan-k/
Sentiment-Analysis-FineTune-HuggingFace