End of training

README.md

@@ -28,11 +28,12 @@ model-index:
 <!-- 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. -->
 
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>]()
 # 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: 0.7953
+- Loss: 1.0125
 - Accuracy: 0.73
 
 ## Model description
@@ -53,8 +54,8 @@ 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: 1
+- eval_batch_size: 1
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -66,14 +67,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.4423        | 1.0   | 450  | 1.2938          | 0.62     |
-| 1.2445        | 2.0   | 900  | 0.9108          | 0.7      |
-| 0.2709        | 3.0   | 1350 | 0.7953          | 0.73     |
+| 1.3647        | 1.0   | 899  | 1.2020          | 0.65     |
+| 1.0999        | 2.0   | 1798 | 1.1490          | 0.7      |
+| 0.1482        | 3.0   | 2697 | 1.0125          | 0.73     |
 
 
 ### Framework versions
 
-- Transformers 4.40.0
+- Transformers 4.41.0.dev0
 - Pytorch 2.2.1+cu121
-- Datasets 2.19.0
+- Datasets 2.17.1
 - Tokenizers 0.19.1