Pushing Data-Lab/rubert-base-cased-conversational_ner-v2 model to Hugging Face Hub
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metadata
base_model: DeepPavlov/rubert-base-cased-conversational
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: rubert-base-cased-conversational_ner-v2
results: []
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: 0.1045
- Precision: 0.9259
- Recall: 0.9375
- F1: 0.9317
- Accuracy: 0.9781
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 | 40 | 0.3025 | 0.6627 | 0.6875 | 0.6748 | 0.9103 |
No log | 2.0 | 80 | 0.1169 | 0.8276 | 0.9 | 0.8623 | 0.9694 |
No log | 3.0 | 120 | 0.1045 | 0.9259 | 0.9375 | 0.9317 | 0.9781 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3