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distilbert-base-cased-finetuned-chunk – AI Model by RobW | AlphaNeural AI
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RobW
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distilbert-base-cased-finetuned-chunk
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transformers
pytorch
tensorboard
distilbert
token-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-cased-finetuned-chunk
This model is a fine-tuned version of
distilbert-base-cased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5180
Precision: 0.8615
Recall: 0.9088
F1: 0.8845
Accuracy: 0.8239
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.8391
1.0
878
0.5871
0.8453
0.9035
0.8734
0.8054
0.6134
2.0
1756
0.5447
0.8555
0.8983
0.8764
0.8142
0.5565
3.0
2634
0.5180
0.8615
0.9088
0.8845
0.8239
Framework versions
Transformers 4.15.0
Pytorch 1.9.1
Tokenizers 0.10.3
