End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/mdeberta-v3-base
+tags:
+- generated_from_trainer
+model-index:
+- name: mdeberta-semeval25_narratives_fold5
+  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. -->
+
+# mdeberta-semeval25_narratives_fold5
+
+This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.0196
+- Precision Samples: 0.3300
+- Recall Samples: 0.8054
+- F1 Samples: 0.4401
+- Precision Macro: 0.6768
+- Recall Macro: 0.5901
+- F1 Macro: 0.3682
+- Precision Micro: 0.2997
+- Recall Micro: 0.7707
+- F1 Micro: 0.4316
+- Precision Weighted: 0.4440
+- Recall Weighted: 0.7707
+- F1 Weighted: 0.3890
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| 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 |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
+| 5.5606        | 1.0   | 19   | 5.1746          | 0.5241            | 0.0760         | 0.0945     | 0.9639          | 0.1737       | 0.1596   | 0.2418          | 0.0827       | 0.1232   | 0.9031             | 0.0827          | 0.0450      |
+| 4.8516        | 2.0   | 38   | 4.9279          | 0.2575            | 0.4866         | 0.3149     | 0.8592          | 0.3182       | 0.2199   | 0.2573          | 0.4323       | 0.3226   | 0.6527             | 0.4323          | 0.1902      |
+| 5.1102        | 3.0   | 57   | 4.6329          | 0.3105            | 0.6392         | 0.3944     | 0.7662          | 0.4137       | 0.2809   | 0.3010          | 0.5827       | 0.3969   | 0.5232             | 0.5827          | 0.2907      |
+| 4.5152        | 4.0   | 76   | 4.4162          | 0.2982            | 0.7060         | 0.3926     | 0.7663          | 0.4692       | 0.2933   | 0.2827          | 0.6654       | 0.3969   | 0.5256             | 0.6654          | 0.3110      |
+| 4.3922        | 5.0   | 95   | 4.2955          | 0.3114            | 0.7290         | 0.4139     | 0.7003          | 0.5100       | 0.3321   | 0.2961          | 0.6880       | 0.4140   | 0.4569             | 0.6880          | 0.3560      |
+| 4.0885        | 6.0   | 114  | 4.1427          | 0.3210            | 0.8169         | 0.4335     | 0.6788          | 0.5895       | 0.3665   | 0.2921          | 0.7820       | 0.4254   | 0.4415             | 0.7820          | 0.3845      |
+| 3.9996        | 7.0   | 133  | 4.0937          | 0.3164            | 0.7928         | 0.4286     | 0.6762          | 0.5803       | 0.3656   | 0.2945          | 0.7594       | 0.4244   | 0.4386             | 0.7594          | 0.3814      |
+| 3.9713        | 8.0   | 152  | 4.0603          | 0.3159            | 0.7847         | 0.4253     | 0.6727          | 0.5768       | 0.3623   | 0.2935          | 0.7481       | 0.4216   | 0.4375             | 0.7481          | 0.3792      |
+| 4.016         | 9.0   | 171  | 4.0393          | 0.3189            | 0.7905         | 0.4300     | 0.6750          | 0.5812       | 0.3654   | 0.2978          | 0.7556       | 0.4272   | 0.4418             | 0.7556          | 0.3848      |
+| 3.9635        | 10.0  | 190  | 4.0196          | 0.3300            | 0.8054         | 0.4401     | 0.6768          | 0.5901       | 0.3682   | 0.2997          | 0.7707       | 0.4316   | 0.4440             | 0.7707          | 0.3890      |
+
+
+### Framework versions
+
+- Transformers 4.46.0
+- Pytorch 2.3.1
+- Datasets 2.21.0
+- Tokenizers 0.20.1

runs/Oct27_16-04-57_icuff-Z790-UD/events.out.tfevents.1730055898.icuff-Z790-UD.501800.8

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