update model card README.md

README.md

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+---
+license: mit
+base_model: microsoft/mdeberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: mdeberta-v3-base-finetuned-climate-classification
+  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-v3-base-finetuned-climate-classification
+
+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: 0.0781
+- Accuracy: 0.9834
+- F1 Macro: 0.9834
+- Accuracy Balanced: 0.9834
+- F1 Micro: 0.9834
+- Precision Macro: 0.9834
+- Recall Macro: 0.9834
+- Precision Micro: 0.9834
+- Recall Micro: 0.9834
+
+## 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: 16
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.06
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
+| 0.1189        | 1.0   | 1918 | 0.0989          | 0.9803   | 0.9803   | 0.9803            | 0.9803   | 0.9803          | 0.9803       | 0.9803          | 0.9803       |
+| 0.0669        | 2.0   | 3836 | 0.0781          | 0.9834   | 0.9834   | 0.9834            | 0.9834   | 0.9834          | 0.9834       | 0.9834          | 0.9834       |
+| 0.0439        | 3.0   | 5754 | 0.0778          | 0.9825   | 0.9825   | 0.9825            | 0.9825   | 0.9825          | 0.9825       | 0.9825          | 0.9825       |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.5.0+cu121
+- Datasets 2.14.7
+- Tokenizers 0.13.3