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Model: adriszmar/whisper-large-v3-turbo-es
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+language:
+- es
+license: mit
+base_model: openai/whisper-large-v3-turbo
+tags:
+- whisper-event
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_17_0
+model-index:
+- name: Whisper Large V3 Turbo - Spanish
+  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 Large V3 Turbo - Spanish
+
+This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 17.0 dataset - spanish subset.
+
+The fine-tuning process reduced the Word Error Rate (WER) from 6.91% to 5.34%, demonstrating significant improvement in transcription accuracy for spanish audios.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+The model was trained using the Common Voice 17.0 dataset - spanish subset (mozilla-foundation/common_voice_17_0). Both the base model, whisper-large-v3-turbo, and the fine-tuned model, whisper-large-v3-turbo-es, were evaluated using Word Error Rate (WER) on the test split of the same dataset. The results are as follows:
+
+- WER for whisper-large-v3-turbo (base): 6.91%
+- WER for whisper-large-v3-turbo-es (fine-tuned): 5.34%
+
+This significant reduction in WER shows that fine-tuning the model for spanish audio led to improved transcription accuracy compared to the original base model.
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 64
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 5000
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "adriszmar/whisper-large-v3-turbo-es",
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "apply_spec_augment": false,
+  "architectures": [
+    "WhisperForConditionalGeneration"
+  ],
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+  "dropout": 0.0,
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+  "mask_feature_min_masks": 0,
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+  "mask_time_prob": 0.05,
+  "max_source_positions": 1500,
+  "max_target_positions": 448,
+  "median_filter_width": 7,
+  "model_type": "whisper",
+  "num_hidden_layers": 32,
+  "num_mel_bins": 128,
+  "pad_token_id": 50257,
+  "scale_embedding": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "use_cache": false,
+  "use_weighted_layer_sum": false,
+  "vocab_size": 51866
+}

generation_config.json

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preprocessor_config.json

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special_tokens_map.json

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