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---
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: rubert-tiny2-odonata-extended-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# rubert-tiny2-odonata-extended-ner
This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0094
- Precision: 0.6364
- Recall: 0.7101
- F1: 0.6712
- Accuracy: 0.9973
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 32 | 0.1433 | 0.0 | 0.0 | 0.0 | 0.9961 |
| No log | 2.0 | 64 | 0.0364 | 0.0 | 0.0 | 0.0 | 0.9961 |
| No log | 3.0 | 96 | 0.0310 | 0.0 | 0.0 | 0.0 | 0.9961 |
| No log | 4.0 | 128 | 0.0286 | 0.0 | 0.0 | 0.0 | 0.9961 |
| No log | 5.0 | 160 | 0.0250 | 0.0 | 0.0 | 0.0 | 0.9961 |
| No log | 6.0 | 192 | 0.0183 | 0.6667 | 0.0290 | 0.0556 | 0.9962 |
| No log | 7.0 | 224 | 0.0141 | 0.5581 | 0.3478 | 0.4286 | 0.9965 |
| No log | 8.0 | 256 | 0.0122 | 0.6111 | 0.4783 | 0.5366 | 0.9969 |
| No log | 9.0 | 288 | 0.0111 | 0.6792 | 0.5217 | 0.5902 | 0.9971 |
| No log | 10.0 | 320 | 0.0105 | 0.6154 | 0.5797 | 0.5970 | 0.9970 |
| No log | 11.0 | 352 | 0.0101 | 0.5857 | 0.5942 | 0.5899 | 0.9971 |
| No log | 12.0 | 384 | 0.0097 | 0.6143 | 0.6232 | 0.6187 | 0.9972 |
| No log | 13.0 | 416 | 0.0096 | 0.6203 | 0.7101 | 0.6622 | 0.9972 |
| No log | 14.0 | 448 | 0.0094 | 0.6282 | 0.7101 | 0.6667 | 0.9973 |
| No log | 15.0 | 480 | 0.0094 | 0.6364 | 0.7101 | 0.6712 | 0.9973 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cpu
- Datasets 2.19.2
- Tokenizers 0.19.1
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