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---
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license: mit
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base_model: cointegrated/rubert-tiny2
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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-tiny2-odonata-extended-ner
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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-tiny2-odonata-extended-ner
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This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0094
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- Precision: 0.6364
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- Recall: 0.7101
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- F1: 0.6712
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- Accuracy: 0.9973
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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: 16
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- eval_batch_size: 16
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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: 15
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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 | 32 | 0.1433 | 0.0 | 0.0 | 0.0 | 0.9961 |
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| No log | 2.0 | 64 | 0.0364 | 0.0 | 0.0 | 0.0 | 0.9961 |
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| No log | 3.0 | 96 | 0.0310 | 0.0 | 0.0 | 0.0 | 0.9961 |
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| No log | 4.0 | 128 | 0.0286 | 0.0 | 0.0 | 0.0 | 0.9961 |
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| No log | 5.0 | 160 | 0.0250 | 0.0 | 0.0 | 0.0 | 0.9961 |
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| No log | 6.0 | 192 | 0.0183 | 0.6667 | 0.0290 | 0.0556 | 0.9962 |
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| No log | 7.0 | 224 | 0.0141 | 0.5581 | 0.3478 | 0.4286 | 0.9965 |
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| No log | 8.0 | 256 | 0.0122 | 0.6111 | 0.4783 | 0.5366 | 0.9969 |
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| No log | 9.0 | 288 | 0.0111 | 0.6792 | 0.5217 | 0.5902 | 0.9971 |
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| No log | 10.0 | 320 | 0.0105 | 0.6154 | 0.5797 | 0.5970 | 0.9970 |
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| No log | 11.0 | 352 | 0.0101 | 0.5857 | 0.5942 | 0.5899 | 0.9971 |
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| No log | 12.0 | 384 | 0.0097 | 0.6143 | 0.6232 | 0.6187 | 0.9972 |
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| No log | 13.0 | 416 | 0.0096 | 0.6203 | 0.7101 | 0.6622 | 0.9972 |
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| No log | 14.0 | 448 | 0.0094 | 0.6282 | 0.7101 | 0.6667 | 0.9973 |
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| No log | 15.0 | 480 | 0.0094 | 0.6364 | 0.7101 | 0.6712 | 0.9973 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.1+cpu
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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