End of training

README.md

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+---
+library_name: transformers
+license: cc-by-nc-4.0
+base_model: nguyenvulebinh/wav2vec2-base-vi
+tags:
+- generated_from_trainer
+datasets:
+- doof-ferb/LSVSC
+metrics:
+- f1
+model-index:
+- name: vietnamese-regional-voice-classification-model
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: LSVSC
+      type: doof-ferb/LSVSC
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.7852888029210245
+---
+
+<!-- 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. -->
+
+# vietnamese-regional-voice-classification-model
+
+This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vi](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vi) on the LSVSC dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6087
+- F1: 0.7853
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 1.0733        | 1.0   | 44   | 0.8828          | 0.7566 |
+| 0.8621        | 2.0   | 88   | 0.7323          | 0.7653 |
+| 0.7834        | 3.0   | 132  | 0.6746          | 0.7992 |
+| 0.7098        | 4.0   | 176  | 0.8050          | 0.6410 |
+| 0.6748        | 5.0   | 220  | 0.7053          | 0.7113 |
+| 0.6335        | 6.0   | 264  | 0.6650          | 0.7491 |
+| 0.6195        | 7.0   | 308  | 0.6096          | 0.7742 |
+| 0.6118        | 8.0   | 352  | 0.6087          | 0.7853 |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

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