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Model: Gummybear05/whisper-small-E50_speed_pause2
Source: Original Platform

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README.md

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+---
+library_name: transformers
+language:
+- hi
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- aihub_adult_baseline
+model-index:
+- name: whisper-small-E50_pause_speed
+  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. -->
+
+# whisper-small-E50_pause_speed
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub old adult freq speed pause changed dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1714
+- Cer: 8.0886
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Cer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.3029        | 0.1289 | 100  | 0.2462          | 6.1971  |
+| 0.161         | 0.2579 | 200  | 0.2166          | 5.6861  |
+| 0.1967        | 0.3868 | 300  | 0.2087          | 5.7625  |
+| 0.1561        | 0.5158 | 400  | 0.2014          | 5.3513  |
+| 0.1372        | 0.6447 | 500  | 0.1973          | 5.5686  |
+| 0.1191        | 0.7737 | 600  | 0.1859          | 5.2455  |
+| 0.1175        | 0.9026 | 700  | 0.1801          | 5.3865  |
+| 0.0697        | 1.0309 | 800  | 0.1754          | 5.1281  |
+| 0.0558        | 1.1599 | 900  | 0.1793          | 4.8578  |
+| 0.0571        | 1.2888 | 1000 | 0.1746          | 4.8931  |
+| 0.0542        | 1.4178 | 1100 | 0.1765          | 5.7096  |
+| 0.0514        | 1.5467 | 1200 | 0.1744          | 7.9300  |
+| 0.0527        | 1.6757 | 1300 | 0.1751          | 9.3867  |
+| 0.0469        | 1.8046 | 1400 | 0.1712          | 12.9171 |
+| 0.0478        | 1.9336 | 1500 | 0.1714          | 8.0886  |
+
+
+### Framework versions
+
+- Transformers 4.47.0.dev0
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

config.json

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+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "apply_spec_augment": false,
+  "architectures": [
+    "WhisperForConditionalGeneration"
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+  "max_length": null,
+  "max_source_positions": 1500,
+  "max_target_positions": 448,
+  "median_filter_width": 7,
+  "model_type": "whisper",
+  "num_hidden_layers": 12,
+  "num_mel_bins": 80,
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+  "torch_dtype": "float32",
+  "transformers_version": "4.47.0.dev0",
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+  "use_weighted_layer_sum": false,
+  "vocab_size": 51865
+}

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