Update README.md

README.md

@@ -1,41 +1,30 @@
 ---
 library_name: transformers
-license: apache-2.0
-base_model: distilbert-base-uncased
-tags:
-- generated_from_trainer
+license: mit
+datasets:
+- fancyzhx/ag_news
+language:
+- en
 metrics:
 - accuracy
-model-index:
-- name: news-clf
-  results: []
+base_model:
+- distilbert/distilbert-base-uncased
+pipeline_tag: text-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. -->
+Classifies English-language news into 4 categories: world, sports, business, and science / technology.
 
-# news-clf
+Fine-tuned version of `distilbert/distilbert-base-uncased` on `fancyzhx/ag_news`, trained for 3 epochs with 128 token truncation.
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.1759
 - Accuracy: 0.9414
 
-## Model description
+Made as a homework project for 4th lesson of the [FastAI's Practical Deep Learning for Coders course](https://course.fast.ai/). Hugging Face Spaces demo available [here](https://huggingface.co/spaces/kitrofimov/news-classifier).
 
-More information needed
+# Training procedure
 
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
+## Training hyperparameters
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
@@ -46,7 +35,7 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 3
 
-### Training results
+## Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
@@ -54,8 +43,7 @@ The following hyperparameters were used during training:
 | 0.1773        | 2.0   | 1876 | 0.1804          | 0.9375   |
 | 0.1418        | 3.0   | 2814 | 0.1759          | 0.9414   |
 
-
-### Framework versions
+## Framework versions
 
 - Transformers 4.56.1
 - Pytorch 2.8.0+cu126