End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: speech-emotion-recognition-with-openai-whisper-large-v3
+  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. -->
+
+# speech-emotion-recognition-with-openai-whisper-large-v3
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5008
+- Accuracy: 0.9199
+- Precision: 0.9230
+- Recall: 0.9199
+- F1: 0.9198
+
+## 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: 5e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 5
+- total_train_batch_size: 10
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 25
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.4948        | 0.9995  | 394  | 0.4911          | 0.8286   | 0.8449    | 0.8286 | 0.8302 |
+| 0.6271        | 1.9990  | 788  | 0.5307          | 0.8225   | 0.8559    | 0.8225 | 0.8277 |
+| 0.2364        | 2.9985  | 1182 | 0.5076          | 0.8692   | 0.8727    | 0.8692 | 0.8684 |
+| 0.0156        | 3.9980  | 1576 | 0.5669          | 0.8732   | 0.8868    | 0.8732 | 0.8745 |
+| 0.2305        | 5.0     | 1971 | 0.4578          | 0.9108   | 0.9142    | 0.9108 | 0.9114 |
+| 0.0112        | 5.9995  | 2365 | 0.4701          | 0.9108   | 0.9159    | 0.9108 | 0.9114 |
+| 0.0013        | 6.9990  | 2759 | 0.5232          | 0.9138   | 0.9204    | 0.9138 | 0.9137 |
+| 0.1894        | 7.9985  | 3153 | 0.5008          | 0.9199   | 0.9230    | 0.9199 | 0.9198 |
+| 0.0877        | 8.9980  | 3547 | 0.5517          | 0.9138   | 0.9152    | 0.9138 | 0.9138 |
+| 0.1471        | 10.0    | 3942 | 0.5856          | 0.8895   | 0.9002    | 0.8895 | 0.8915 |
+| 0.0026        | 10.9995 | 4336 | 0.8334          | 0.8773   | 0.8949    | 0.8773 | 0.8770 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

model.safetensors

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