Model save

README.md

@@ -0,0 +1,85 @@
+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- accuracy
+model-index:
+- name: violence-audio-Recognition-666
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9645748987854251
+---
+
+<!-- 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. -->
+
+# violence-audio-Recognition-666
+
+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: 0.1258
+- Accuracy: 0.9646
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4755        | 0.99  | 61   | 0.3227          | 0.8715   |
+| 0.2665        | 1.99  | 123  | 0.2088          | 0.9322   |
+| 0.1808        | 3.0   | 185  | 0.1783          | 0.9474   |
+| 0.1505        | 4.0   | 247  | 0.1528          | 0.9504   |
+| 0.1158        | 4.99  | 308  | 0.1260          | 0.9615   |
+| 0.0928        | 5.99  | 370  | 0.1302          | 0.9656   |
+| 0.0792        | 7.0   | 432  | 0.1327          | 0.9626   |
+| 0.0707        | 7.9   | 488  | 0.1258          | 0.9646   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1280809b1f9f4bd81b3bb1c1cbe1994b401f14ee9886fe4a805845a2a89a9a59
+oid sha256:a064a8e1f83b081b042463fe2f2f68287af084b84c16e8b52bff735fdcb01e59
 size 378302360

runs/Apr12_16-53-30_0beb97ad9549/events.out.tfevents.1712940811.0beb97ad9549.179.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:004643619056fb035f7ccf45a3c20943ad52647c969ba9313daf396b5cebaf68
-size 10723
+oid sha256:6b41b7a1efb7a43a16d0f03bb4629c4b9191c6a7868a7327c87a9e6e5a4ae9f0
+size 11077