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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_narratives09_maxf1_fold3
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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_narratives09_maxf1_fold3
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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: 4.1972
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- Precision Samples: 0.3634
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- Recall Samples: 0.7451
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- F1 Samples: 0.4586
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- Precision Macro: 0.6979
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- Recall Macro: 0.4621
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- F1 Macro: 0.2857
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- Precision Micro: 0.3270
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- Recall Micro: 0.6974
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- F1 Micro: 0.4452
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- Precision Weighted: 0.4846
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- Recall Weighted: 0.6974
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- F1 Weighted: 0.3864
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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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| 5.6486 | 1.0 | 19 | 5.3335 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0476 | 0.0476 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
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| 5.1544 | 2.0 | 38 | 5.1485 | 0.3023 | 0.3614 | 0.2993 | 0.8755 | 0.1773 | 0.1289 | 0.2996 | 0.3063 | 0.3029 | 0.7138 | 0.3063 | 0.1870 |
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| 4.8667 | 3.0 | 57 | 4.9432 | 0.2776 | 0.4614 | 0.3282 | 0.8665 | 0.2238 | 0.1327 | 0.2853 | 0.4022 | 0.3338 | 0.6952 | 0.4022 | 0.1947 |
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| 4.5126 | 4.0 | 76 | 4.6697 | 0.3487 | 0.5930 | 0.4045 | 0.7826 | 0.2967 | 0.1944 | 0.3166 | 0.5129 | 0.3915 | 0.5781 | 0.5129 | 0.2876 |
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| 4.6317 | 5.0 | 95 | 4.4823 | 0.3405 | 0.6624 | 0.4196 | 0.7583 | 0.3672 | 0.2290 | 0.3034 | 0.5978 | 0.4025 | 0.5513 | 0.5978 | 0.3219 |
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| 4.4113 | 6.0 | 114 | 4.3402 | 0.3574 | 0.7394 | 0.4481 | 0.7165 | 0.4305 | 0.2537 | 0.3140 | 0.6790 | 0.4294 | 0.4928 | 0.6790 | 0.3587 |
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| 3.9755 | 7.0 | 133 | 4.2814 | 0.3659 | 0.7354 | 0.4539 | 0.7175 | 0.4258 | 0.2523 | 0.3176 | 0.6716 | 0.4313 | 0.4960 | 0.6716 | 0.3581 |
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| 4.0457 | 8.0 | 152 | 4.2820 | 0.3549 | 0.7009 | 0.4398 | 0.7116 | 0.4227 | 0.2646 | 0.32 | 0.6494 | 0.4287 | 0.4905 | 0.6494 | 0.3644 |
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| 4.0695 | 9.0 | 171 | 4.1947 | 0.3767 | 0.7511 | 0.4662 | 0.7109 | 0.4572 | 0.2863 | 0.3259 | 0.7011 | 0.4450 | 0.4949 | 0.7011 | 0.3884 |
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| 4.3445 | 10.0 | 190 | 4.1972 | 0.3634 | 0.7451 | 0.4586 | 0.6979 | 0.4621 | 0.2857 | 0.3270 | 0.6974 | 0.4452 | 0.4846 | 0.6974 | 0.3864 |
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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_17-47-09_icuff-Z790-UD/events.out.tfevents.1730062031.icuff-Z790-UD.556423.4
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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 19894
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