Update README.md

README.md

@@ -1,71 +1,43 @@
 ---
-library_name: transformers
-license: apache-2.0
-base_model: distilbert-base-uncased
+language:
+- en
+license: other
 tags:
-- generated_from_trainer
-metrics:
-- accuracy
-- f1
-- precision
-- recall
-model-index:
-- name: finetuning_text_model
-  results: []
+- text
+- youtube
+- comments
+- music
+- text-classification
+annotations_creators:
+- human-annotated
+- machine-generated
+language_creators:
+- found
+pretty_name: YouTube Music Comments (Original & Augmented)
+task_categories:
+- text-classification
+task_ids:
+- multi-class-classification
 ---
 
-<!-- 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. -->
-
-# finetuning_text_model
-
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0422
-- Accuracy: 1.0
-- F1: 1.0
-- Precision: 1.0
-- Recall: 1.0
-
-## 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: 8
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: linear
-- num_epochs: 5
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 1.2278        | 1.0   | 84   | 1.0599          | 0.9048   | 0.9030 | 0.9148    | 0.9048 |
-| 0.509         | 2.0   | 168  | 0.3537          | 0.9821   | 0.9820 | 0.9829    | 0.9821 |
-| 0.1262        | 3.0   | 252  | 0.1090          | 0.9881   | 0.9881 | 0.9883    | 0.9881 |
-| 0.0686        | 4.0   | 336  | 0.0548          | 0.9940   | 0.9940 | 0.9943    | 0.9940 |
-| 0.0469        | 5.0   | 420  | 0.0482          | 0.9940   | 0.9940 | 0.9943    | 0.9940 |
-
-
-### Framework versions
-
-- Transformers 4.56.1
-- Pytorch 2.8.0+cu126
-- Datasets 4.0.0
-- Tokenizers 0.22.0
+# YouTube Music Comments (Original & Augmented)
+
+**Summary:** User comments from YouTube music videos labeled with one of 7 genres  
+(`pop`, `Jazz`, `rock`, `electronic`, `R&B`, `Metal`, `Classical`). Two splits are provided:
+`original` (human-labeled) and `augmented` (synthetic additions), both with columns:
+- `text` (string)
+- `label` (string)
+
+## Load
+```python
+from datasets import load_dataset
+ds = load_dataset("Iris314/Youtube_music_comments")
+original  = ds["original"]
+augmented = ds["augmented"]
+
+@misc{youtube_music_comments_2025,
+  title        = {YouTube Music Comments (Original & Augmented)},
+  author       = {Iris314},
+  year         = {2025},
+  howpublished = {\url{https://huggingface.co/datasets/Iris314/Youtube_music_comments}}
+}