End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- minds14
+metrics:
+- accuracy
+model-index:
+- name: my_first_audio_cls
+  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: 0.02654867256637168
+---
+
+<!-- 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. -->
+
+# my_first_audio_cls
+
+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: 2.6974
+- Accuracy: 0.0265
+
+## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.8   | 3    | 2.6409          | 0.0708   |
+| No log        | 1.8   | 6    | 2.6526          | 0.0442   |
+| No log        | 2.8   | 9    | 2.6640          | 0.0354   |
+| 12.1127       | 3.8   | 12   | 2.6773          | 0.0354   |
+| 12.1127       | 4.8   | 15   | 2.6847          | 0.0265   |
+| 12.1127       | 5.8   | 18   | 2.6889          | 0.0177   |
+| 12.0275       | 6.8   | 21   | 2.6939          | 0.0265   |
+| 12.0275       | 7.8   | 24   | 2.6953          | 0.0265   |
+| 12.0275       | 8.8   | 27   | 2.6968          | 0.0265   |
+| 11.9952       | 9.8   | 30   | 2.6974          | 0.0265   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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