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_maxf1_fold4
+  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_maxf1_fold4
+
+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: 9.5014
+- Precision Samples: 0.1859
+- Recall Samples: 0.4699
+- F1 Samples: 0.2429
+- Precision Macro: 0.8926
+- Recall Macro: 0.3346
+- F1 Macro: 0.2682
+- Precision Micro: 0.1665
+- Recall Micro: 0.3667
+- F1 Micro: 0.2290
+- Precision Weighted: 0.6548
+- Recall Weighted: 0.3667
+- F1 Weighted: 0.1249
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
+| 10.3744       | 1.0   | 19   | 10.7628         | 0.8966            | 0.0276         | 0.0276     | 0.9912          | 0.2349       | 0.2352   | 0.2105          | 0.0111       | 0.0211   | 0.9364             | 0.0111          | 0.0134      |
+| 10.0964       | 2.0   | 38   | 10.4150         | 0.1931            | 0.2487         | 0.2006     | 0.9819          | 0.2551       | 0.2402   | 0.1855          | 0.1417       | 0.1606   | 0.8825             | 0.1417          | 0.0452      |
+| 9.7497        | 3.0   | 57   | 10.2289         | 0.1563            | 0.3064         | 0.1883     | 0.9622          | 0.2717       | 0.2444   | 0.1528          | 0.1889       | 0.1689   | 0.8281             | 0.1889          | 0.0564      |
+| 9.5354        | 4.0   | 76   | 10.0861         | 0.1637            | 0.3508         | 0.2028     | 0.9368          | 0.2875       | 0.2527   | 0.1555          | 0.2389       | 0.1884   | 0.7498             | 0.2389          | 0.0850      |
+| 9.4556        | 5.0   | 95   | 9.8949          | 0.1741            | 0.4008         | 0.2220     | 0.9182          | 0.3137       | 0.2614   | 0.1610          | 0.3139       | 0.2128   | 0.7027             | 0.3139          | 0.1085      |
+| 8.9584        | 6.0   | 114  | 9.7492          | 0.1781            | 0.4272         | 0.2286     | 0.9166          | 0.3207       | 0.2604   | 0.1565          | 0.3333       | 0.2130   | 0.6984             | 0.3333          | 0.1062      |
+| 8.7492        | 7.0   | 133  | 9.6473          | 0.1947            | 0.4416         | 0.2409     | 0.9160          | 0.3267       | 0.2654   | 0.1647          | 0.35         | 0.224    | 0.6963             | 0.35            | 0.1186      |
+| 8.2566        | 8.0   | 152  | 9.5650          | 0.1889            | 0.4622         | 0.2434     | 0.8985          | 0.3328       | 0.2666   | 0.1690          | 0.3639       | 0.2308   | 0.6673             | 0.3639          | 0.1223      |
+| 8.7461        | 9.0   | 171  | 9.5200          | 0.1842            | 0.4668         | 0.2406     | 0.8925          | 0.3325       | 0.2680   | 0.1665          | 0.3611       | 0.2279   | 0.6552             | 0.3611          | 0.1250      |
+| 8.5201        | 10.0  | 190  | 9.5014          | 0.1859            | 0.4699         | 0.2429     | 0.8926          | 0.3346       | 0.2682   | 0.1665          | 0.3667       | 0.2290   | 0.6548             | 0.3667          | 0.1249      |
+
+
+### Framework versions
+
+- Transformers 4.46.0
+- Pytorch 2.3.1
+- Datasets 2.21.0
+- Tokenizers 0.20.1

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