End of training

README.md

@@ -0,0 +1,92 @@
+---
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+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: 0.86
+---
+
+<!-- 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: 0.7337
+- Accuracy: 0.86
+
+## 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: 6e-05
+- train_batch_size: 6
+- eval_batch_size: 6
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 12
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.1397        | 1.0   | 75   | 2.0011          | 0.45     |
+| 1.4889        | 2.0   | 150  | 1.3599          | 0.66     |
+| 1.0109        | 3.0   | 225  | 1.0052          | 0.74     |
+| 0.7499        | 4.0   | 300  | 0.8884          | 0.77     |
+| 0.5627        | 5.0   | 375  | 0.6333          | 0.86     |
+| 0.4138        | 6.0   | 450  | 0.5492          | 0.81     |
+| 0.2909        | 7.0   | 525  | 0.6417          | 0.81     |
+| 0.1475        | 8.0   | 600  | 0.5900          | 0.84     |
+| 0.0845        | 9.0   | 675  | 0.6959          | 0.84     |
+| 0.0619        | 10.0  | 750  | 0.6587          | 0.86     |
+| 0.0233        | 11.0  | 825  | 0.7675          | 0.82     |
+| 0.0168        | 12.0  | 900  | 0.7352          | 0.83     |
+| 0.0152        | 13.0  | 975  | 0.7293          | 0.87     |
+| 0.0136        | 14.0  | 1050 | 0.7490          | 0.86     |
+| 0.0123        | 15.0  | 1125 | 0.7337          | 0.86     |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5ddb94eac7f8a92786f1e936fb57d56e455c9549ed3b2c823349ef0b51253dbd
+oid sha256:201f897216be4cddca8f4a071e130e60ef226932deec057f6cc12ff8cfcbf82e
 size 94783376