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wsklee/
distilbert-sentiment-imdb-cft

Name: distilbert-sentiment-imdb-cft
Availability: InStock

transformers

safetensors

distilbert

generated_from_trainer

distilbert/distilbert-base-uncased

finetune

apache-2.0

endpoints_compatible

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distilbert-sentiment-imdb-cft

This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Accuracy: 0.9856
Pos Similarity: 0.9538
Neg Similarity: 0.4913
F1: 0.9927
Precision: 1.0
Recall: 0.9856
Loss: 3.5397

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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_ratio: 0.1
num_epochs: 4

Training results

Training Loss	Epoch	Step	Accuracy	Pos Similarity	Neg Similarity	F1	Precision	Recall	Validation Loss
3.8563	1.1364	200	0.9728	0.9662	0.7048	0.9862	1.0	0.9728	3.5778
3.5857	2.2727	400	0.9848	0.9666	0.5691	0.9923	1.0	0.9848	3.5278
3.5032	3.4091	600	0.9856	0.9538	0.4913	0.9927	1.0	0.9856	3.5397

Framework versions

Transformers 4.46.2
Pytorch 2.5.1
Datasets 3.1.0
Tokenizers 0.20.3

wsklee/distilbert-sentiment-imdb-cft

distilbert-sentiment-imdb-cft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

wsklee/
distilbert-sentiment-imdb-cft