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rubert-base-cased-conversational_ner-v1 – AI Model by Data-Lab | AlphaNeural AI
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rubert-base-cased-conversational_ner-v1
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transformers
pytorch
bert
token-classification
generated_from_trainer
DeepPavlov/rubert-base-cased-conversational
finetune
autotrain_compatible
endpoints_compatible
us
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rubert-base-cased-conversational_ner-v2
This model is a fine-tuned version of
DeepPavlov/rubert-base-cased-conversational
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1360
Precision: 0.7324
Recall: 0.7939
F1: 0.7619
Accuracy: 0.9289
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
No log
1.0
60
0.2248
0.5069
0.5573
0.5309
0.8591
No log
2.0
120
0.1435
0.6966
0.7710
0.7319
0.9289
No log
3.0
180
0.1360
0.7324
0.7939
0.7619
0.9289
Framework versions
Transformers 4.33.1
Pytorch 2.0.1
Datasets 2.14.4
Tokenizers 0.13.3
