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Pushing Data-Lab/rubert-base-cased-conversational_ner-v2 model to Hugging Face Hub
Browse files- README.md +67 -0
- pytorch_model.bin +1 -1
README.md
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---
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base_model: DeepPavlov/rubert-base-cased-conversational
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: rubert-base-cased-conversational_ner-v2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# rubert-base-cased-conversational_ner-v2
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This model is a fine-tuned version of [DeepPavlov/rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1045
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- Precision: 0.9259
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- Recall: 0.9375
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- F1: 0.9317
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- Accuracy: 0.9781
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 40 | 0.3025 | 0.6627 | 0.6875 | 0.6748 | 0.9103 |
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| No log | 2.0 | 80 | 0.1169 | 0.8276 | 0.9 | 0.8623 | 0.9694 |
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| No log | 3.0 | 120 | 0.1045 | 0.9259 | 0.9375 | 0.9317 | 0.9781 |
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### Framework versions
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- Transformers 4.33.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size 709134505
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version https://git-lfs.github.com/spec/v1
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size 709134505
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