Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- f1
+- precision
+- recall
+model-index:
+- name: 1.0.0
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: initial_audio
+      split: test
+      args: initial_audio
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.11428571428571428
+    - name: Precision
+      type: precision
+      value: 0.6666666666666666
+    - name: Recall
+      type: recall
+      value: 0.0625
+---
+
+<!-- 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. -->
+
+# 1.0.0
+
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6934
+- F1: 0.1143
+- Precision: 0.6667
+- Recall: 0.0625
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 2    | 0.6925          | 0.1176 | 1.0       | 0.0625 |
+| No log        | 2.0   | 4    | 0.6929          | 0.1081 | 0.4       | 0.0625 |
+| No log        | 3.0   | 6    | 0.6934          | 0.1143 | 0.6667    | 0.0625 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1
+- Datasets 3.0.0
+- Tokenizers 0.19.1

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