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bert-finetuned-radarr – AI Model by Servarr | AlphaNeural AI
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bert-finetuned-radarr
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transformers
pytorch
tensorboard
distilbert
token-classification
generated_from_trainer
movie_releases
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-radarr
This model is a fine-tuned version of
distilbert-base-uncased
on the movie_releases dataset. It achieves the following results on the evaluation set:
Loss: 0.0731
Precision: 0.9555
Recall: 0.9639
F1: 0.9597
Accuracy: 0.9818
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0431
1.0
1191
0.1403
0.9436
0.9574
0.9504
0.9626
0.0236
2.0
2382
0.0881
0.9485
0.9560
0.9522
0.9694
0.0138
3.0
3573
0.0731
0.9555
0.9639
0.9597
0.9818
Framework versions
Transformers 4.20.1
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1
