Model save

README.md

@@ -0,0 +1,72 @@
+---
+library_name: transformers
+license: mit
+base_model: microsoft/mdeberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: mdeberta-v3-base-finetuned-french-green-stance
+  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-french-green-stance
+
+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: 0.3085
+- Accuracy: 0.9533
+- F1 Macro: 0.9428
+- Accuracy Balanced: 0.9425
+- F1 Micro: 0.9533
+- Precision Macro: 0.9431
+- Recall Macro: 0.9425
+- Precision Micro: 0.9533
+- Recall Micro: 0.9533
+
+## 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: 4
+- eval_batch_size: 4
+- 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
+- lr_scheduler_warmup_ratio: 0.06
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
+| 0.3304        | 1.0   | 1393 | 0.4028          | 0.9160   | 0.8984   | 0.9035            | 0.9160   | 0.8937          | 0.9035       | 0.9160          | 0.9160       |
+| 0.2085        | 2.0   | 2786 | 0.2895          | 0.9440   | 0.9298   | 0.9201            | 0.9440   | 0.9410          | 0.9201       | 0.9440          | 0.9440       |
+| 0.1368        | 3.0   | 4179 | 0.3136          | 0.9519   | 0.9408   | 0.9384            | 0.9519   | 0.9432          | 0.9384       | 0.9519          | 0.9519       |
+| 0.0374        | 4.0   | 5572 | 0.3085          | 0.9533   | 0.9428   | 0.9425            | 0.9533   | 0.9431          | 0.9425       | 0.9533          | 0.9533       |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.0