End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/hubert-base-ls960
+tags:
+- generated_from_trainer
+datasets:
+- common_language
+metrics:
+- accuracy
+model-index:
+- name: hubert-base-ls960-finetuned-common_language-finetuned-common_language
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: Common Language
+      type: common_language
+      config: full
+      split: test
+      args: full
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8011068254234446
+---
+
+<!-- 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. -->
+
+# hubert-base-ls960-finetuned-common_language-finetuned-common_language
+
+This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the Common Language dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4164
+- Accuracy: 0.8011
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 2.9713        | 1.0   | 2774  | 3.0764          | 0.1615   |
+| 1.7443        | 2.0   | 5549  | 1.8279          | 0.4734   |
+| 1.1304        | 3.0   | 8323  | 1.3202          | 0.6371   |
+| 1.2718        | 4.0   | 11098 | 1.1571          | 0.6968   |
+| 0.769         | 5.0   | 13872 | 1.2917          | 0.7127   |
+| 0.2656        | 6.0   | 16647 | 1.1549          | 0.7479   |
+| 0.2939        | 7.0   | 19421 | 1.2372          | 0.7736   |
+| 0.1278        | 8.0   | 22196 | 1.2985          | 0.7875   |
+| 0.5175        | 9.0   | 24970 | 1.3664          | 0.7986   |
+| 0.0547        | 10.0  | 27740 | 1.4164          | 0.8011   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3