End of training

README.md

@@ -6,35 +6,17 @@ tags:
 - generated_from_trainer
 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: 0.77
+- name: distilhubert-finetuned-gtzan-6
+  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
+# distilhubert-finetuned-gtzan-6
 
 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: 0.9845
-- Accuracy: 0.77
 
 ## Model description
 
@@ -54,33 +36,18 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 2
-- eval_batch_size: 2
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 10
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.7838        | 1.0   | 450  | 1.6025          | 0.46     |
-| 0.7936        | 2.0   | 900  | 1.2049          | 0.6      |
-| 0.4021        | 3.0   | 1350 | 1.0288          | 0.66     |
-| 1.1686        | 4.0   | 1800 | 0.8219          | 0.74     |
-| 0.0712        | 5.0   | 2250 | 0.8418          | 0.76     |
-| 0.0278        | 6.0   | 2700 | 0.9047          | 0.76     |
-| 0.0097        | 7.0   | 3150 | 0.9742          | 0.73     |
-| 0.0102        | 8.0   | 3600 | 0.9556          | 0.77     |
-| 0.0062        | 9.0   | 4050 | 0.9434          | 0.78     |
-| 0.0098        | 10.0  | 4500 | 0.9845          | 0.77     |
-
+- mixed_precision_training: Native AMP
 
 ### Framework versions
 
-- Transformers 4.48.3
-- Pytorch 2.6.0
-- Datasets 3.2.0
-- Tokenizers 0.21.0
+- Transformers 4.50.2
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c5b39b53849144c87a16eb75f5e861ea1d3cc0d888f88bd247fde1d72a648945
+oid sha256:ff335948ef97922913fe3e29b73e74a88ecec50199e216138a3357ff099e3291
 size 94771728