End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-large-xlsr-53-dialect-classifier
+  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-dialect-classifier
+
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3693
+- Accuracy: 0.3605
+
+## 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: 1e-05
+- train_batch_size: 4
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.3719        | 0.98  | 21   | 1.3693          | 0.3605   |
+| 1.371         | 2.0   | 43   | 1.3652          | 0.3605   |
+| 1.3638        | 2.98  | 64   | 1.3588          | 0.3605   |
+| 1.3571        | 4.0   | 86   | 1.3508          | 0.3605   |
+| 1.3446        | 4.98  | 107  | 1.3440          | 0.3605   |
+| 1.3399        | 6.0   | 129  | 1.3388          | 0.3605   |
+| 1.3303        | 6.98  | 150  | 1.3340          | 0.3605   |
+| 1.3305        | 8.0   | 172  | 1.3305          | 0.3605   |
+| 1.334         | 8.98  | 193  | 1.3267          | 0.3605   |
+| 1.3303        | 10.0  | 215  | 1.3232          | 0.3605   |
+| 1.3241        | 10.98 | 236  | 1.3205          | 0.3605   |
+| 1.317         | 12.0  | 258  | 1.3183          | 0.3605   |
+| 1.3239        | 12.98 | 279  | 1.3161          | 0.3605   |
+| 1.3169        | 14.0  | 301  | 1.3144          | 0.3605   |
+| 1.3129        | 14.98 | 322  | 1.3128          | 0.3605   |
+| 1.3112        | 16.0  | 344  | 1.3115          | 0.3605   |
+| 1.3231        | 16.98 | 365  | 1.3107          | 0.3605   |
+| 1.3115        | 18.0  | 387  | 1.3099          | 0.3605   |
+| 1.3082        | 18.98 | 408  | 1.3092          | 0.3605   |
+| 1.3228        | 20.0  | 430  | 1.3085          | 0.3605   |
+| 1.2872        | 20.98 | 451  | 1.3080          | 0.3605   |
+| 1.2744        | 22.0  | 473  | 1.3075          | 0.3605   |
+| 1.2835        | 22.98 | 494  | 1.3070          | 0.3605   |
+| 1.3213        | 24.0  | 516  | 1.3068          | 0.3605   |
+| 1.3112        | 24.98 | 537  | 1.3065          | 0.3605   |
+| 1.3047        | 26.0  | 559  | 1.3062          | 0.3605   |
+| 1.29          | 26.98 | 580  | 1.3061          | 0.3605   |
+| 1.3114        | 28.0  | 602  | 1.3060          | 0.3605   |
+| 1.3123        | 28.98 | 623  | 1.3060          | 0.3605   |
+| 1.3217        | 29.3  | 630  | 1.3060          | 0.3605   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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