End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-base-finetuned-Speaker-Classification
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: data
+      split: test
+      args: data
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9834791059280855
+---
+
+<!-- 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. -->
+
+# wav2vec2-base-finetuned-Speaker-Classification
+
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0927
+- Accuracy: 0.9835
+
+## 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: 10
+- eval_batch_size: 10
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 40
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3234        | 0.99  | 102  | 0.2863          | 0.9349   |
+| 0.2465        | 2.0   | 205  | 0.1983          | 0.9563   |
+| 0.1184        | 3.0   | 308  | 0.1599          | 0.9670   |
+| 0.0753        | 4.0   | 411  | 0.0927          | 0.9835   |
+| 0.0549        | 4.96  | 510  | 0.1025          | 0.9786   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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