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trained_baseline – AI Model by annamariagnat | AlphaNeural AI
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annamariagnat
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trained_baseline
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transformers
safetensors
distilbert
token-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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trained_baseline
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:
Loss: 0.0834
Precision: 0.7505
Recall: 0.7625
F1: 0.7565
Accuracy: 0.9782
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
0.1292
1.0
784
0.0785
0.6897
0.7603
0.7233
0.9755
0.0321
2.0
1568
0.0778
0.7370
0.7691
0.7527
0.9776
0.0211
3.0
2352
0.0834
0.7505
0.7625
0.7565
0.9782
Framework versions
Transformers 4.38.2
Pytorch 2.1.2+cu118
Datasets 2.18.0
Tokenizers 0.15.2
