Update README.md

README.md

@@ -28,11 +28,6 @@ such as multi-label classification, covariate shift or self-supervised learning.
 
 ## 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.
-This results in approximately double the disk usage for each dataset. While it is possible to manually delete all files not contained in the <code>extracted</code>
- folder, 
-we are actively working on updating the builder script to resolve this issue.
-
 |                                | #train recordings   |    #test labels    | #test_5s segments |  size (GB) |   #classes   |   
 |--------------------------------|--------:|-----------:|--------:|-----------:|-------------:|
 | [PER][1] (Amazon Basin + XCL Subset)        |  16,802 |     14,798 |  15,120 |   10.5     |     132      |  
@@ -121,6 +116,32 @@ train = dataset["train"].map(map_first_five, batch_size=1000, num_proc=2)
 test = dataset["test_5s"]
 ```
 
+## 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")
+```
+
 ## Metadata
 
 |                        | format                                                 |    description           | 
@@ -238,31 +259,6 @@ 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