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_narratives09_fold2
+  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_narratives09_fold2
+
+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: 4.2915
+- Precision Samples: 0.3850
+- Recall Samples: 0.7226
+- F1 Samples: 0.4627
+- Precision Macro: 0.7130
+- Recall Macro: 0.4503
+- F1 Macro: 0.2846
+- Precision Micro: 0.3282
+- Recall Micro: 0.6957
+- F1 Micro: 0.4460
+- Precision Weighted: 0.4983
+- Recall Weighted: 0.6957
+- F1 Weighted: 0.3925
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
+| 5.4789        | 1.0   | 19   | 5.4030          | 1.0               | 0.0            | 0.0        | 1.0             | 0.0476       | 0.0476   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
+| 5.2627        | 2.0   | 38   | 5.1901          | 0.2839            | 0.3351         | 0.2805     | 0.9014          | 0.1655       | 0.1112   | 0.2952          | 0.2899       | 0.2925   | 0.7607             | 0.2899          | 0.1520      |
+| 4.6993        | 3.0   | 57   | 5.0001          | 0.3075            | 0.4274         | 0.3272     | 0.8700          | 0.2042       | 0.1344   | 0.3164          | 0.3841       | 0.3470   | 0.6843             | 0.3841          | 0.2124      |
+| 4.5547        | 4.0   | 76   | 4.7741          | 0.3603            | 0.5142         | 0.3949     | 0.8024          | 0.2616       | 0.1705   | 0.3290          | 0.4601       | 0.3837   | 0.5941             | 0.4601          | 0.2529      |
+| 4.2228        | 5.0   | 95   | 4.5899          | 0.3432            | 0.6239         | 0.4110     | 0.7733          | 0.3356       | 0.2028   | 0.3165          | 0.5688       | 0.4067   | 0.5551             | 0.5688          | 0.3071      |
+| 4.0369        | 6.0   | 114  | 4.4640          | 0.3575            | 0.6764         | 0.4282     | 0.7161          | 0.3926       | 0.2391   | 0.3084          | 0.6413       | 0.4165   | 0.4951             | 0.6413          | 0.3492      |
+| 4.0052        | 7.0   | 133  | 4.3708          | 0.3529            | 0.6907         | 0.4313     | 0.7169          | 0.4237       | 0.2521   | 0.3088          | 0.6703       | 0.4229   | 0.4941             | 0.6703          | 0.3594      |
+| 3.8847        | 8.0   | 152  | 4.3291          | 0.3645            | 0.7105         | 0.4445     | 0.7205          | 0.4312       | 0.2569   | 0.3170          | 0.6812       | 0.4327   | 0.5006             | 0.6812          | 0.3678      |
+| 3.8223        | 9.0   | 171  | 4.3064          | 0.3676            | 0.7080         | 0.4457     | 0.7196          | 0.4326       | 0.2643   | 0.3160          | 0.6812       | 0.4317   | 0.4985             | 0.6812          | 0.3716      |
+| 4.3457        | 10.0  | 190  | 4.2915          | 0.3850            | 0.7226         | 0.4627     | 0.7130          | 0.4503       | 0.2846   | 0.3282          | 0.6957       | 0.4460   | 0.4983             | 0.6957          | 0.3925      |
+
+
+### Framework versions
+
+- Transformers 4.46.0
+- Pytorch 2.3.1
+- Datasets 2.21.0
+- Tokenizers 0.20.1

runs/Oct27_16-41-41_icuff-Z790-UD/events.out.tfevents.1730058102.icuff-Z790-UD.525411.2

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