Update README.md

README.md

@@ -26,26 +26,6 @@ such as multi-label classification, covariate shift or self-supervised learning.
 - **Complementary Code**: [Repository](https://github.com/DBD-research-group/BirdSet)
 - **Complementary Paper**: [ArXiv Link](https://arxiv.org/abs/2403.10380)
 
-## Update (2024.12.06)
-- **This only works for datasets<3.0.0!**
-- The [data download size descrepancy](https://github.com/DBD-research-group/BirdSet/issues/267) has been solved.
-- TL;DR: During the extraction process, unnecessary archives are now removed immediately. This reduces the required disk space by *half*, now aligning it with the table below.
-- Note: If you downloaded the data between this and last update and don't want to update, you can use the following `revision=b0c14a03571a7d73d56b12c4b1db81952c4f7e64`:
-```python
-from datasets import load_dataset
-ds = load_dataset("DBD-research-group/BirdSet", "HSN", trust_remote_code=True, revision="b0c14a03571a7d73d56b12c4b1db81952c4f7e64")
-```
-## Update (2024.11.27)
-- Additional bird taxonomy metadata, including "Genus," "Species Group," and "Order," is provided using the 2021 eBird taxonomy, consistent with the taxonomy used for the 'ebird_code' data. 
-  These metadata fields follow the same format and encoding as 'ebird_code' and 'ebird_code_multilabel'. See below for an updated explanation of the metadata.
-- If you don't require the additional taxonomy at the moment and prefer to avoid re-downloading all files, you can specify the previous revision directly in load_dataset as follows:
-```python
-from datasets import load_dataset
-ds = load_dataset("DBD-research-group/BirdSet", "HSN", trust_remote_code=True, revision="629b54c06874b6d2fa886e1c0d73146c975612d0")
-```
-
-
-
 ## Datasets
 
 **Disclaimer on sizes**: The current dataset sizes reflect the extracted files, as the builder script automatically extracts these files but retains the original zipped versions.
@@ -258,13 +238,39 @@ test = dataset["test_5s"]
  'order_multilabel': [5]}}
 ```
 
+### Changelog
+
+## 2025.09.10
+- Updated dataset description and citation in BirdSet.py
+- Now works with datasets<4.0.0
+  - `load_dataset(..., cache_dir="/path/to/custom/cache")` almost works like in previous datasets<3.0.0 version. 
+    With the different that archive files are downloaded to `HF_HOME/HF_DATASETS` environment variable path but extracted file are save in cache_dir if specified.
+    During extraction archive files are still deleted during extraction, see previous update/issue, to save disk space.
+
+## 2024.12.06
+- The [data download size descrepancy](https://github.com/DBD-research-group/BirdSet/issues/267) has been solved.
+- TL;DR: During the extraction process, unnecessary archives are now removed immediately. This reduces the required disk space by *half*, now aligning it with the table below.
+- Note: If you downloaded the data between this and last update and don't want to update, you can use the following `revision=b0c14a03571a7d73d56b12c4b1db81952c4f7e64`:
+```python
+from datasets import load_dataset
+ds = load_dataset("DBD-research-group/BirdSet", "HSN", trust_remote_code=True, revision="b0c14a03571a7d73d56b12c4b1db81952c4f7e64")
+```
+## 2024.11.27
+- Additional bird taxonomy metadata, including "Genus," "Species Group," and "Order," is provided using the 2021 eBird taxonomy, consistent with the taxonomy used for the 'ebird_code' data. 
+  These metadata fields follow the same format and encoding as 'ebird_code' and 'ebird_code_multilabel'. See below for an updated explanation of the metadata.
+- If you don't require the additional taxonomy at the moment and prefer to avoid re-downloading all files, you can specify the previous revision directly in load_dataset as follows:
+```python
+from datasets import load_dataset
+ds = load_dataset("DBD-research-group/BirdSet", "HSN", trust_remote_code=True, revision="629b54c06874b6d2fa886e1c0d73146c975612d0")
+```
+
 ### Citation Information
 
 ```
-@misc{rauch2024birdsetlargescaledatasetaudio,
+@misc{rauch2025birdsetlargescaledatasetaudio,
       title={BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics}, 
       author={Lukas Rauch and Raphael Schwinger and Moritz Wirth and René Heinrich and Denis Huseljic and Marek Herde and Jonas Lange and Stefan Kahl and Bernhard Sick and Sven Tomforde and Christoph Scholz},
-      year={2024},
+      year={2025},
       eprint={2403.10380},
       archivePrefix={arXiv},
       primaryClass={cs.SD},