Re-add my commit with my best results (9d65f1419f0e87aa21be9fdf72ca8bcb9a395367) after adding a task tag

README.md

@@ -3,86 +3,35 @@ license: apache-2.0
 base_model: ntu-spml/distilhubert
 tags:
 - generated_from_trainer
-- audio-classification
 datasets:
 - marsyas/gtzan
-metrics:
-- accuracy
+
+
 model-index:
 - name: distilhubert-finetuned-gtzan
-  results:
-  - task:
-      name: Audio Classification
-      type: audio-classification
-    dataset:
-      name: GTZAN
-      type: marsyas/gtzan
-      config: all
-      split: train
-      args: all
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.85
+  results: []
 ---
 
 <!-- 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. -->
-
-# distilhubert-finetuned-gtzan
 
 This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5797
-- Accuracy: 0.85
+- eval_loss: 0.5534
+- eval_accuracy: 0.88
+- eval_runtime: 66.8648
+- eval_samples_per_second: 1.496
+- eval_steps_per_second: 0.194
+- epoch: 1.0
+- step: 113
 
 ## 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: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 11
+- num_epochs: 9
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9767        | 1.0   | 113  | 1.8825          | 0.53     |
-| 1.1647        | 2.0   | 226  | 1.3428          | 0.62     |
-| 1.0652        | 3.0   | 339  | 1.0057          | 0.7      |
-| 0.6664        | 4.0   | 452  | 0.8889          | 0.72     |
-| 0.5592        | 5.0   | 565  | 0.6754          | 0.81     |
-| 0.3939        | 6.0   | 678  | 0.6415          | 0.84     |
-| 0.2753        | 7.0   | 791  | 0.6098          | 0.84     |
-| 0.1135        | 8.0   | 904  | 0.6292          | 0.83     |
-| 0.1878        | 9.0   | 1017 | 0.5693          | 0.86     |
-| 0.0864        | 10.0  | 1130 | 0.6220          | 0.83     |
-| 0.0685        | 11.0  | 1243 | 0.5797          | 0.85     |
-
-
 ### Framework versions
 
 - Transformers 4.44.0
 - Pytorch 2.4.0
-- Datasets 3.0.0
+- Datasets 2.21.0
 - Tokenizers 0.19.1