Model save

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: wav2vec2-base-finetuned-common_voice
+  results: []
+---
+
+<!-- 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-common_voice
+
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0419
+- Accuracy: 0.995
+- F1: 0.9950
+- Recall: 0.9950
+- Precision: 0.9951
+- Mcc: 0.9938
+- Auc: 0.9987
+
+## 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: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision | Mcc    | Auc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
+| 0.8258        | 1.0   | 200  | 0.7423          | 0.76     | 0.6973 | 0.76   | 0.6699    | 0.7402 | 0.9766 |
+| 0.1609        | 2.0   | 400  | 0.1559          | 0.96     | 0.9596 | 0.96   | 0.9644    | 0.9513 | 0.9997 |
+| 0.219         | 3.0   | 600  | 0.0864          | 0.9825   | 0.9826 | 0.9825 | 0.9828    | 0.9782 | 0.9983 |
+| 0.0049        | 4.0   | 800  | 0.0341          | 0.995    | 0.9950 | 0.9950 | 0.9950    | 0.9938 | 0.9999 |
+| 0.0031        | 5.0   | 1000 | 0.1241          | 0.98     | 0.9799 | 0.9800 | 0.9808    | 0.9752 | 0.9989 |
+| 0.0021        | 6.0   | 1200 | 0.0394          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9988 |
+| 0.0017        | 7.0   | 1400 | 0.0410          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9993 |
+| 0.0015        | 8.0   | 1600 | 0.0420          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9987 |
+| 0.0013        | 9.0   | 1800 | 0.0418          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9987 |
+| 0.0013        | 10.0  | 2000 | 0.0419          | 0.995    | 0.9950 | 0.9950 | 0.9951    | 0.9938 | 0.9987 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

model.safetensors

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