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-aug-fold-4
+  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-aug-fold-4
+
+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: 4.4212
+- Accuracy: 0.0162
+- Precision: 0.0003
+- Recall: 0.0162
+- F1: 0.0005
+- Binary: 0.1372
+
+## 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: 0.0001
+- 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: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Binary |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
+| No log        | 0.19  | 50   | 4.4257          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+| No log        | 0.38  | 100  | 4.4274          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1261 |
+| No log        | 0.58  | 150  | 4.4261          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1243 |
+| No log        | 0.77  | 200  | 4.4265          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1261 |
+| No log        | 0.96  | 250  | 4.4254          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+| 4.44          | 1.15  | 300  | 4.4262          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+| 4.44          | 1.34  | 350  | 4.4259          | 0.0108   | 0.0001    | 0.0108 | 0.0002 | 0.1296 |
+| 4.44          | 1.53  | 400  | 4.4249          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1315 |
+| 4.44          | 1.73  | 450  | 4.4237          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+| 4.44          | 1.92  | 500  | 4.4235          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+| 4.4196        | 2.11  | 550  | 4.4231          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1261 |
+| 4.4196        | 2.3   | 600  | 4.4243          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1253 |
+| 4.4196        | 2.49  | 650  | 4.4258          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1261 |
+| 4.4196        | 2.68  | 700  | 4.4226          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+| 4.4196        | 2.88  | 750  | 4.4225          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+| 4.4188        | 3.07  | 800  | 4.4240          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+| 4.4188        | 3.26  | 850  | 4.4240          | 0.0135   | 0.0002    | 0.0135 | 0.0004 | 0.1334 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.3.0
+- Datasets 2.19.1
+- Tokenizers 0.15.1

runs/Jun27_18-41-18_LAPTOP-1GID9RGH/events.out.tfevents.1719488479.LAPTOP-1GID9RGH.19012.8

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