Create README.md

README.md

@@ -0,0 +1,51 @@
+---
+license: mit
+language:
+- uz
+metrics:
+- precision
+- recall
+- f1
+base_model:
+- FacebookAI/xlm-roberta-base
+library_name: transformers
+---
+
+# xlm-roberta-base-lowercase
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.16673
+- Precision: 0.5710
+- Recall: 0.6137
+- F1: 0.5916
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 2
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Use 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_steps: 500
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
+| 0.1949        | 1.0   | 2206 | 0.1788          | 0.5315    | 0.5391 | 0.5353 |
+| 0.1669        | 2.0   | 4412 | 0.1670          | 0.5353    | 0.5995 | 0.5656 |
+| 0.1361        | 3.0   | 6618 | 0.1667          | 0.5710    | 0.6137 | 0.5916 |
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.3.1
+- Tokenizers 0.21.0