End of training

README.md

@@ -1,62 +1,60 @@
----
-library_name: transformers
-license: apache-2.0
-base_model: ntu-spml/distilhubert
-tags:
-- generated_from_trainer
-datasets:
-- marsyas/gtzan
-model-index:
-- name: distilhubert-regularized-gtzan
-  results: []
-metrics:
-- accuracy
----
-
-<!-- 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-regularized-gtzan
-
-This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the marsyas/gtzan dataset.
-It achieves the following results on the evaluation set:
-- eval_loss: 0.6969
-- eval_model_preparation_time: 0.0031
-- eval_accuracy: 0.86
-- eval_runtime: 69.8954
-- eval_samples_per_second: 1.431
-- eval_steps_per_second: 0.186
-- step: 0
-
-## 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: 3e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- 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: 0.2
-- num_epochs: 30
-
-### Framework versions
-
-- Transformers 4.48.0.dev0
-- Pytorch 2.6.0+cu126
-- Datasets 3.2.0
-- Tokenizers 0.21.0
+---
+library_name: transformers
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+model-index:
+- name: distilhubert-finetuned-hyperparam-gtzan
+  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-hyperparam-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:
+- eval_loss: 0.6969
+- eval_model_preparation_time: 0.0031
+- eval_accuracy: 0.86
+- eval_runtime: 69.8954
+- eval_samples_per_second: 1.431
+- eval_steps_per_second: 0.186
+- step: 0
+
+## 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: 3e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- 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: 0.2
+- num_epochs: 30
+
+### Framework versions
+
+- Transformers 4.48.0.dev0
+- Pytorch 2.6.0+cu126
+- Datasets 3.2.0
+- Tokenizers 0.21.0