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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: 0.0226
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- Precision: 0.5313
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- Recall: 0.551
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- F1: 0.5410
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- Accuracy: 0.9930
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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 | 0.1425 | 0.0 | 0.0 | 0.0 | 0.9910 |
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| No log | 2.0 | 64 | 0.0643 | 0.0 | 0.0 | 0.0 | 0.9910 |
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| No log | 3.0 | 96 | 0.0604 | 0.0 | 0.0 | 0.0 | 0.9910 |
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| No log | 4.0 | 128 | 0.0575 | 0.0 | 0.0 | 0.0 | 0.9910 |
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| No log | 5.0 | 160 | 0.0523 | 0.0 | 0.0 | 0.0 | 0.9910 |
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| No log | 6.0 | 192 | 0.0427 | 0.0 | 0.0 | 0.0 | 0.9910 |
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| No log | 7.0 | 224 | 0.0330 | 0.7753 | 0.069 | 0.1267 | 0.9913 |
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| No log | 8.0 | 256 | 0.0288 | 0.6309 | 0.376 | 0.4712 | 0.9921 |
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| No log | 9.0 | 288 | 0.0264 | 0.6145 | 0.373 | 0.4642 | 0.9924 |
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| No log | 10.0 | 320 | 0.0251 | 0.5489 | 0.432 | 0.4835 | 0.9926 |
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| No log | 11.0 | 352 | 0.0242 | 0.5354 | 0.484 | 0.5084 | 0.9927 |
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| No log | 12.0 | 384 | 0.0235 | 0.5393 | 0.515 | 0.5269 | 0.9928 |
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| No log | 13.0 | 416 | 0.0230 | 0.5310 | 0.54 | 0.5354 | 0.9929 |
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| No log | 14.0 | 448 | 0.0228 | 0.5287 | 0.553 | 0.5406 | 0.9930 |
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| No log | 15.0 | 480 | 0.0226 | 0.5313 | 0.551 | 0.5410 | 0.9930 |
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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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