End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- minds14
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-base-finetuned-minds-1
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: minds14
+      type: minds14
+      config: en-US
+      split: train
+      args: en-US
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7610619469026548
+---
+
+<!-- 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-minds-1
+
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4208
+- Accuracy: 0.7611
+
+## 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: 5e-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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.6059        | 1.0   | 57   | 2.5954          | 0.0973   |
+| 2.5183        | 2.0   | 114  | 2.5787          | 0.0973   |
+| 2.5497        | 3.0   | 171  | 2.5629          | 0.1416   |
+| 2.3827        | 4.0   | 228  | 2.5407          | 0.1858   |
+| 2.309         | 5.0   | 285  | 2.3023          | 0.2301   |
+| 2.0098        | 6.0   | 342  | 2.0528          | 0.3540   |
+| 1.797         | 7.0   | 399  | 1.8558          | 0.4602   |
+| 1.4416        | 8.0   | 456  | 1.6847          | 0.5841   |
+| 1.3491        | 9.0   | 513  | 1.4911          | 0.6991   |
+| 1.3468        | 10.0  | 570  | 1.4208          | 0.7611   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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