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End of training
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README.md
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---
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library_name: transformers
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license: mit
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base_model: microsoft/mdeberta-v3-base
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tags:
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- generated_from_trainer
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model-index:
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- name: mdeberta-semeval25_maxf1_fold2
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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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# mdeberta-semeval25_maxf1_fold2
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This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 8.8694
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- Precision Samples: 0.1448
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- Recall Samples: 0.4710
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- F1 Samples: 0.2054
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- Precision Macro: 0.8790
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- Recall Macro: 0.3070
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- F1 Macro: 0.2198
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- Precision Micro: 0.1280
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- Recall Micro: 0.3545
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- F1 Micro: 0.1881
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- Precision Weighted: 0.6566
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- Recall Weighted: 0.3545
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- F1 Weighted: 0.1024
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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: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision Samples | Recall Samples | F1 Samples | Precision Macro | Recall Macro | F1 Macro | Precision Micro | Recall Micro | F1 Micro | Precision Weighted | Recall Weighted | F1 Weighted |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
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| 10.355 | 1.0 | 19 | 9.8646 | 0.4690 | 0.1586 | 0.1586 | 0.9914 | 0.1974 | 0.1928 | 0.23 | 0.0697 | 0.1070 | 0.9300 | 0.0697 | 0.0322 |
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| 10.0042 | 2.0 | 38 | 9.5711 | 0.1517 | 0.2663 | 0.1814 | 0.9710 | 0.2144 | 0.1962 | 0.1493 | 0.1515 | 0.1504 | 0.8541 | 0.1515 | 0.0453 |
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| 9.8111 | 3.0 | 57 | 9.4447 | 0.1190 | 0.31 | 0.1625 | 0.9497 | 0.2248 | 0.1978 | 0.1202 | 0.1818 | 0.1448 | 0.7968 | 0.1818 | 0.0506 |
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| 9.5882 | 4.0 | 76 | 9.3361 | 0.1149 | 0.3593 | 0.1645 | 0.9292 | 0.2427 | 0.2010 | 0.1124 | 0.2333 | 0.1517 | 0.7463 | 0.2333 | 0.0586 |
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| 9.2717 | 5.0 | 95 | 9.2287 | 0.1179 | 0.3825 | 0.1684 | 0.8992 | 0.2584 | 0.2061 | 0.1135 | 0.2667 | 0.1593 | 0.6898 | 0.2667 | 0.0697 |
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| 9.4865 | 6.0 | 114 | 9.1175 | 0.1358 | 0.4366 | 0.1948 | 0.9025 | 0.2876 | 0.2179 | 0.1253 | 0.3182 | 0.1798 | 0.6965 | 0.3182 | 0.0869 |
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| 9.2006 | 7.0 | 133 | 8.9906 | 0.1428 | 0.4627 | 0.2029 | 0.8891 | 0.3008 | 0.2184 | 0.1275 | 0.3455 | 0.1863 | 0.6810 | 0.3455 | 0.0981 |
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| 9.0527 | 8.0 | 152 | 8.9299 | 0.1434 | 0.4696 | 0.2040 | 0.8874 | 0.3057 | 0.2181 | 0.1271 | 0.3515 | 0.1866 | 0.6767 | 0.3515 | 0.0977 |
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| 9.3313 | 9.0 | 171 | 8.8794 | 0.1450 | 0.4727 | 0.2053 | 0.8803 | 0.3092 | 0.2203 | 0.1280 | 0.3576 | 0.1885 | 0.6602 | 0.3576 | 0.1037 |
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| 8.4989 | 10.0 | 190 | 8.8694 | 0.1448 | 0.4710 | 0.2054 | 0.8790 | 0.3070 | 0.2198 | 0.1280 | 0.3545 | 0.1881 | 0.6566 | 0.3545 | 0.1024 |
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### Framework versions
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- Transformers 4.46.0
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- Pytorch 2.3.1
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- Datasets 2.21.0
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- Tokenizers 0.20.1
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runs/Oct27_18-05-30_icuff-Z790-UD/events.out.tfevents.1730063131.icuff-Z790-UD.569991.2
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 22740
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