Create README.md

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+datasets:
+- Alant2000/taiga_cleared
+metrics:
+- accuracy
+model-index:
+- name: output
+  results:
+  - task:
+      name: Causal Language Modeling
+      type: text-generation
+    dataset:
+      name: Alant2000/taiga_cleared
+      type: Alant2000/taiga_cleared
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.3070757857382329
+---
+
+Модель обучена в рамках практического задания по курсу "Практические аспекты обучения LLM": https://github.com/RefalMachine/rcc_msu_llm_course_autumn_2024/tree/main
+
+This model is a fine-tuned version of ruadapt_qwen2.5_1.5B_ext_u48_mean_init on the [Alant2000/taiga_cleared](https://huggingface.co/datasets/Alant2000/taiga_cleared) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.0484
+- Accuracy: 0.3071
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 16
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 1024
+- total_eval_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| No log        | 0.0008 | 1    | 7.8632          | 0.1493   |
+| 4.0503        | 0.7593 | 1000 | 4.0488          | 0.3070   |
+
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
+- Datasets 2.18.0
+- Tokenizers 0.20.3