Model save

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: deeepfake-audio-c
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9247311827956989
+---
+
+<!-- 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. -->
+
+# deeepfake-audio-c
+
+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: 0.3276
+- Accuracy: 0.9247
+
+## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6297        | 1.0   | 46   | 0.5694          | 0.7849   |
+| 0.461         | 2.0   | 92   | 0.4060          | 0.8602   |
+| 0.3332        | 3.0   | 138  | 0.5541          | 0.7849   |
+| 0.2591        | 4.0   | 184  | 0.3564          | 0.8817   |
+| 0.179         | 5.0   | 230  | 0.1679          | 0.9570   |
+| 0.1563        | 6.0   | 276  | 0.2795          | 0.9355   |
+| 0.1129        | 7.0   | 322  | 0.3251          | 0.9247   |
+| 0.0786        | 8.0   | 368  | 0.3276          | 0.9247   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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