Model save

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: wav2vec2-large-xlsr-53-finetuned-ks
+  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-large-xlsr-53-finetuned-ks
+
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4923
+- Accuracy: 0.7871
+- F1: 0.7863
+
+## 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
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 1.379         | 1.0   | 141  | 1.3767          | 0.2991   | 0.1377 |
+| 1.3611        | 2.0   | 283  | 1.3600          | 0.2991   | 0.1377 |
+| 1.3393        | 3.0   | 424  | 1.3515          | 0.2991   | 0.1377 |
+| 1.2932        | 4.0   | 566  | 1.3306          | 0.3607   | 0.3098 |
+| 1.2356        | 5.0   | 707  | 1.2202          | 0.4397   | 0.3926 |
+| 1.2222        | 6.0   | 849  | 1.3719          | 0.3601   | 0.2778 |
+| 1.036         | 7.0   | 990  | 1.2779          | 0.4290   | 0.3781 |
+| 1.0348        | 8.0   | 1132 | 1.2845          | 0.4257   | 0.3824 |
+| 0.9044        | 9.0   | 1273 | 1.2239          | 0.4927   | 0.4646 |
+| 0.8557        | 10.0  | 1415 | 1.6261          | 0.3926   | 0.3253 |
+| 0.804         | 11.0  | 1556 | 1.0748          | 0.5703   | 0.5558 |
+| 0.6517        | 12.0  | 1698 | 1.2891          | 0.5471   | 0.5294 |
+| 0.6063        | 13.0  | 1839 | 0.9921          | 0.6552   | 0.6514 |
+| 0.5008        | 14.0  | 1981 | 1.4346          | 0.5391   | 0.5162 |
+| 0.5425        | 15.0  | 2122 | 1.3406          | 0.5802   | 0.5573 |
+| 0.3806        | 16.0  | 2264 | 1.2260          | 0.6353   | 0.6291 |
+| 0.4022        | 17.0  | 2405 | 1.7530          | 0.5444   | 0.5197 |
+| 0.3001        | 18.0  | 2547 | 1.3619          | 0.6247   | 0.6132 |
+| 0.1921        | 19.0  | 2688 | 1.3687          | 0.6505   | 0.6443 |
+| 0.2704        | 20.0  | 2830 | 1.2533          | 0.6810   | 0.6745 |
+| 0.3145        | 21.0  | 2971 | 1.6079          | 0.6233   | 0.6133 |
+| 0.2045        | 22.0  | 3113 | 1.1432          | 0.7215   | 0.7198 |
+| 0.2444        | 23.0  | 3254 | 1.4012          | 0.6936   | 0.6861 |
+| 0.2223        | 24.0  | 3396 | 1.5944          | 0.6585   | 0.6533 |
+| 0.2415        | 25.0  | 3537 | 1.1057          | 0.7454   | 0.7420 |
+| 0.2233        | 26.0  | 3679 | 1.4083          | 0.7036   | 0.6997 |
+| 0.119         | 27.0  | 3820 | 1.3240          | 0.7341   | 0.7323 |
+| 0.1125        | 28.0  | 3962 | 1.8332          | 0.6658   | 0.6590 |
+| 0.1577        | 29.0  | 4103 | 1.8048          | 0.6764   | 0.6714 |
+| 0.1169        | 30.0  | 4245 | 1.3329          | 0.7573   | 0.7563 |
+| 0.1348        | 31.0  | 4386 | 2.0588          | 0.6485   | 0.6359 |
+| 0.1203        | 32.0  | 4528 | 1.6487          | 0.7082   | 0.7012 |
+| 0.1262        | 33.0  | 4669 | 1.5428          | 0.7261   | 0.7236 |
+| 0.0679        | 34.0  | 4811 | 1.5458          | 0.7374   | 0.7357 |
+| 0.0741        | 35.0  | 4952 | 1.4596          | 0.7546   | 0.7508 |
+| 0.0913        | 36.0  | 5094 | 1.3710          | 0.7699   | 0.7702 |
+| 0.2104        | 37.0  | 5235 | 1.6693          | 0.7367   | 0.7344 |
+| 0.0856        | 38.0  | 5377 | 1.6339          | 0.75     | 0.7483 |
+| 0.0931        | 39.0  | 5518 | 1.6512          | 0.7580   | 0.7571 |
+| 0.0613        | 40.0  | 5660 | 1.6046          | 0.7646   | 0.7638 |
+| 0.0713        | 41.0  | 5801 | 1.4553          | 0.7785   | 0.7779 |
+| 0.025         | 42.0  | 5943 | 1.5725          | 0.7639   | 0.7625 |
+| 0.0811        | 43.0  | 6084 | 1.7562          | 0.75     | 0.7474 |
+| 0.0315        | 44.0  | 6226 | 1.4923          | 0.7871   | 0.7863 |
+| 0.1026        | 45.0  | 6367 | 1.6013          | 0.7712   | 0.7706 |
+| 0.0489        | 46.0  | 6509 | 1.7439          | 0.7533   | 0.7502 |
+| 0.0248        | 47.0  | 6650 | 1.6019          | 0.7745   | 0.7730 |
+| 0.0269        | 48.0  | 6792 | 1.6128          | 0.7679   | 0.7659 |
+| 0.0114        | 49.0  | 6933 | 1.5737          | 0.7798   | 0.7788 |
+| 0.0609        | 49.82 | 7050 | 1.6570          | 0.7712   | 0.7692 |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.1+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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