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---
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_model_
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. -->
# my_awesome_wnut_model_
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: 0.1997
- Precision: 0.3076
- Recall: 0.4690
- F1: 0.3716
- Accuracy: 0.9322
## 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: 7
- eval_batch_size: 7
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 24
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.621 | 2.41 | 140 | 0.4025 | 0.0 | 0.0 | 0.0 | 0.9050 |
| 0.3224 | 4.83 | 280 | 0.2750 | 0.2036 | 0.2074 | 0.2055 | 0.9118 |
| 0.2421 | 7.24 | 420 | 0.2326 | 0.2706 | 0.3406 | 0.3016 | 0.9220 |
| 0.2061 | 9.66 | 560 | 0.2146 | 0.2968 | 0.4102 | 0.3444 | 0.9269 |
| 0.1779 | 12.07 | 700 | 0.2037 | 0.3125 | 0.4257 | 0.3604 | 0.9306 |
| 0.1606 | 14.48 | 840 | 0.2042 | 0.3044 | 0.4613 | 0.3668 | 0.9298 |
| 0.1544 | 16.9 | 980 | 0.2001 | 0.3101 | 0.4690 | 0.3734 | 0.9310 |
| 0.1402 | 19.31 | 1120 | 0.1991 | 0.3130 | 0.4690 | 0.3755 | 0.9316 |
| 0.139 | 21.72 | 1260 | 0.1997 | 0.3076 | 0.4690 | 0.3716 | 0.9322 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
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