End of training

README.md

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+---
+base_model: HariprasathSB/indic-whisper-vulnerable
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: audio-abuse-feature
+  results: []
+---
+
+<!-- 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. -->
+
+# audio-abuse-feature
+
+This model is a fine-tuned version of [HariprasathSB/indic-whisper-vulnerable](https://huggingface.co/HariprasathSB/indic-whisper-vulnerable) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4489
+- Accuracy: 0.8814
+- Macro Precision: 0.8557
+- Macro Recall: 0.8472
+- Macro F1-score: 0.8513
+
+## 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: 1e-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: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Macro Precision | Macro Recall | Macro F1-score |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------------:|
+| 0.4633        | 0.4367 | 50   | 0.3753          | 0.8327   | 0.8321          | 0.8314       | 0.8317         |
+| 0.345         | 0.8734 | 100  | 0.4170          | 0.8241   | 0.8612          | 0.8126       | 0.8150         |
+| 0.2592        | 1.3100 | 150  | 0.3357          | 0.8512   | 0.8506          | 0.8502       | 0.8504         |
+| 0.2097        | 1.7467 | 200  | 0.3142          | 0.8758   | 0.8757          | 0.8744       | 0.8749         |
+| 0.1545        | 2.1834 | 250  | 0.3551          | 0.8721   | 0.8713          | 0.8718       | 0.8715         |
+| 0.0829        | 2.6201 | 300  | 0.3916          | 0.8795   | 0.8797          | 0.8778       | 0.8786         |
+| 0.0944        | 3.0568 | 350  | 0.4137          | 0.8721   | 0.8714          | 0.8730       | 0.8718         |
+| 0.0416        | 3.4934 | 400  | 0.5350          | 0.8659   | 0.8677          | 0.8631       | 0.8646         |
+| 0.0469        | 3.9301 | 450  | 0.5129          | 0.8733   | 0.8727          | 0.8726       | 0.8727         |
+| 0.0247        | 4.3668 | 500  | 0.5543          | 0.8708   | 0.8713          | 0.8689       | 0.8698         |
+| 0.0208        | 4.8035 | 550  | 0.5611          | 0.8696   | 0.8691          | 0.8688       | 0.8689         |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

model.safetensors

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+size 1229957888

preprocessor_config.json

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+{
+  "chunk_length": 30,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 80,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "WhisperProcessor",
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}

training_args.bin

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