End of training

README.md

@@ -0,0 +1,85 @@
+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- minds14
+metrics:
+- accuracy
+model-index:
+- name: my_awesome_mind_model
+  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: 0.05309734513274336
+---
+
+<!-- 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_awesome_mind_model
+
+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: 2.6632
+- Accuracy: 0.0531
+
+## 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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.8   | 3    | 2.6455          | 0.0531   |
+| No log        | 1.87  | 7    | 2.6547          | 0.0708   |
+| 2.6354        | 2.93  | 11   | 2.6574          | 0.0796   |
+| 2.6354        | 4.0   | 15   | 2.6594          | 0.0531   |
+| 2.6354        | 4.8   | 18   | 2.6640          | 0.0442   |
+| 2.6333        | 5.87  | 22   | 2.6637          | 0.0619   |
+| 2.6333        | 6.93  | 26   | 2.6632          | 0.0531   |
+| 2.626         | 8.0   | 30   | 2.6632          | 0.0531   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0
+- Datasets 2.17.0
+- Tokenizers 0.15.2

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