End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/hubert-base-ls960
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: hubert-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. -->
+
+# hubert-classifier
+
+This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.2824
+- Accuracy: 0.1864
+- Precision: 0.1087
+- Recall: 0.1864
+- F1: 0.1114
+- Binary: 0.4189
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Binary |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
+| No log        | 0.86  | 50   | 4.2455          | 0.0533   | 0.0410    | 0.0533 | 0.0255 | 0.3252 |
+| No log        | 1.72  | 100  | 3.9851          | 0.0630   | 0.0179    | 0.0630 | 0.0163 | 0.3249 |
+| No log        | 2.59  | 150  | 3.7681          | 0.0726   | 0.0401    | 0.0726 | 0.0283 | 0.3421 |
+| No log        | 3.45  | 200  | 3.7448          | 0.0678   | 0.0383    | 0.0678 | 0.0252 | 0.3167 |
+| No log        | 4.31  | 250  | 3.5775          | 0.0896   | 0.0447    | 0.0896 | 0.0413 | 0.3453 |
+| No log        | 5.17  | 300  | 3.5078          | 0.0969   | 0.0380    | 0.0969 | 0.0400 | 0.3482 |
+| No log        | 6.03  | 350  | 3.4008          | 0.1283   | 0.0445    | 0.1283 | 0.0587 | 0.3777 |
+| No log        | 6.9   | 400  | 3.3443          | 0.1550   | 0.1089    | 0.1550 | 0.0850 | 0.3983 |
+| No log        | 7.76  | 450  | 3.2965          | 0.1792   | 0.1052    | 0.1792 | 0.1056 | 0.4177 |
+| 3.768         | 8.62  | 500  | 3.2824          | 0.1864   | 0.1087    | 0.1864 | 0.1114 | 0.4189 |
+| 3.768         | 9.48  | 550  | 3.2609          | 0.2058   | 0.1339    | 0.2058 | 0.1251 | 0.4332 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.3.0
+- Datasets 2.19.1
+- Tokenizers 0.15.1

runs/Jun13_13-23-20_LAPTOP-1GID9RGH/events.out.tfevents.1718259800.LAPTOP-1GID9RGH.9068.0

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runs/Jun13_13-23-20_LAPTOP-1GID9RGH/events.out.tfevents.1718260129.LAPTOP-1GID9RGH.9068.1

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