Commit
Β·
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Parent(s):
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Subindo arquivos
Browse files- README.md +69 -7
- app.py +64 -0
- requirements.txt +5 -0
- results/config.json +110 -0
- results/model.safetensors +3 -0
- results/preprocessor_config.json +10 -0
- results/special_tokens_map.json +6 -0
- results/tokenizer_config.json +50 -0
- results/vocab.json +34 -0
README.md
CHANGED
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---
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title: Speech
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emoji:
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colorFrom:
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colorTo:
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sdk: gradio
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sdk_version: 4.
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app_file: app.py
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pinned: false
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license: ecl-2.0
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---
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-
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---
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title: Speech-accent-es-classifier
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emoji: ποΈπ€πͺπΈ
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colorFrom: blue
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colorTo: purple
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sdk: gradio
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sdk_version: "4.12.0"
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app_file: app.py
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pinned: false
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---
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# Clasificador de Sotaques en EspaΓ±ol
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Este proyecto es un clasificador de acentos que distingue entre el espaΓ±ol y otros acentos.
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## Resumen del Proyecto
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Esta aplicaciΓ³n utiliza un modelo entrenado para clasificar acentos de habla en dos categorΓas:
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1. EspaΓ±ol
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2. Otro
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El modelo se basa en el trabajo del autor y utiliza la parte en espaΓ±ol del conjunto de datos Common Voice (versiΓ³n 11.0) de la FundaciΓ³n Mozilla.
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## Conjunto de Datos
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El proyecto utiliza el subconjunto en espaΓ±ol del conjunto de datos Common Voice:
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- Conjunto de datos: "mozilla-foundation/common_voice_11_0", "es"
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Acentos espaΓ±oles incluidos en el conjunto de datos:
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- EspaΓ±a
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- MΓ©xico
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- Colombia
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- Argentina
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- Chile
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- PerΓΊ
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- Venezuela
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- Cuba
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- RepΓΊblica Dominicana
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- Uruguay
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- Paraguay
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- Bolivia
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- Ecuador
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- Guatemala
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- Honduras
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- El Salvador
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- Nicaragua
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- Costa Rica
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- PanamΓ‘
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- Puerto Rico
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## Detalles TΓ©cnicos
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El proyecto utiliza el siguiente modelo y procesador:
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- Modelo: "facebook/wav2vec2-base-960h"
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- Procesador: Wav2Vec2Processor.from_pretrained
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## Licencia
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ecl
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## InformaciΓ³n del Desarrollador
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Desarrollado por Ramon Mayor Martins, Ph.D. (2024)
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- Correo electrΓ³nico: [email protected]
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- PΓ‘gina web: https://rmayormartins.github.io/
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- Twitter: @rmayormartins
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- GitHub: https://github.com/rmayormartins
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## Agradecimientos
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Agradecimientos especiales al Instituto Federal de Santa Catarina (Instituto Federal de Santa Catarina) IFSC-SΓ£o JosΓ©-Brasil.
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## Contacto
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Para cualquier consulta o sugerencia, por favor contacte al desarrollador usando la informaciΓ³n proporcionada arriba.
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app.py
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import gradio as gr
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import torch
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import numpy as np
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from transformers import Wav2Vec2Processor, Wav2Vec2ForSequenceClassification
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#
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model_name = "results"
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processor = Wav2Vec2Processor.from_pretrained(model_name)
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model = Wav2Vec2ForSequenceClassification.from_pretrained(model_name)
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def classify_accent(audio):
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if audio is None:
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return "Error: No se recibiΓ³ audio"
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# Entrada
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print(f"Tipo de entrada de audio: {type(audio)}")
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# O Γ‘udio formato
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print(f"Entrada de audio recibida: {audio}")
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try:
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audio_array = audio[1] #
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sample_rate = audio[0] #
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print(f"Forma del audio: {audio_array.shape}, Frecuencia de muestreo: {sample_rate}")
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#
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audio_array = audio_array.astype(np.float32)
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#
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if sample_rate != 16000:
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import librosa
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audio_array = librosa.resample(audio_array, orig_sr=sample_rate, target_sr=16000)
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input_values = processor(audio_array, return_tensors="pt", sampling_rate=16000).input_values
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# Infer
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with torch.no_grad():
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logits = model(input_values).logits
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predicted_ids = torch.argmax(logits, dim=-1).item()
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#
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labels = ["EspaΓ±ol", "Otro"]
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return labels[predicted_ids]
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except Exception as e:
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return f"Error al procesar el audio: {str(e)}"
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#
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description_html = """
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<p>Prueba con grabaciΓ³n o cargando un archivo de audio. Para probar, recomiendo una palabra.</p>
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<p>Ramon Mayor Martins, Ph.D.: <a href="https://rmayormartins.github.io/" target="_blank">Website</a> | <a href="https://huggingface.co/rmayormartins" target="_blank">Spaces</a></p>
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"""
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#
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interface = gr.Interface(
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fn=classify_accent,
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inputs=gr.Audio(type="numpy"),
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outputs="label",
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title="Clasificador de Sotaques (EspaΓ±ol vs Otro)",
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description=description_html
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)
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interface.launch()
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requirements.txt
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gradio==4.29.0
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torch==2.0.1
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numpy==1.23.5
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transformers==4.24.0
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librosa==0.9.2
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results/config.json
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{
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"_name_or_path": "facebook/wav2vec2-base-960h",
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"activation_dropout": 0.1,
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"adapter_attn_dim": null,
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"adapter_kernel_size": 3,
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"adapter_stride": 2,
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"add_adapter": false,
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"apply_spec_augment": true,
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"architectures": [
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"Wav2Vec2ForSequenceClassification"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 1,
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"classifier_proj_size": 256,
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"codevector_dim": 256,
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"contrastive_logits_temperature": 0.1,
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"conv_bias": false,
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"conv_dim": [
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512,
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512,
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512,
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512,
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512,
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512,
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512
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],
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"conv_kernel": [
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10,
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3,
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3,
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3,
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3,
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2,
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2
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],
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"conv_stride": [
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5,
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2,
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2,
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2,
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2,
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2,
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+
2
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],
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"ctc_loss_reduction": "sum",
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"ctc_zero_infinity": false,
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"diversity_loss_weight": 0.1,
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"do_stable_layer_norm": false,
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"eos_token_id": 2,
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"feat_extract_activation": "gelu",
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"feat_extract_dropout": 0.0,
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"feat_extract_norm": "group",
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"feat_proj_dropout": 0.1,
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"feat_quantizer_dropout": 0.0,
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"final_dropout": 0.1,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout": 0.1,
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+
"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.1,
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"mask_feature_length": 10,
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+
"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.05,
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"model_type": "wav2vec2",
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"num_adapter_layers": 3,
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"num_attention_heads": 12,
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"num_codevector_groups": 2,
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"num_codevectors_per_group": 320,
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+
"num_conv_pos_embedding_groups": 16,
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+
"num_conv_pos_embeddings": 128,
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+
"num_feat_extract_layers": 7,
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"num_hidden_layers": 12,
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"num_negatives": 100,
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"output_hidden_size": 768,
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"pad_token_id": 0,
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"proj_codevector_dim": 256,
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"tdnn_dilation": [
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1,
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2,
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3,
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1,
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1
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],
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"tdnn_dim": [
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512,
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512,
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512,
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512,
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1500
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],
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"tdnn_kernel": [
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5,
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+
3,
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3,
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1,
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1
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],
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"torch_dtype": "float32",
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+
"transformers_version": "4.43.4",
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"use_weighted_layer_sum": false,
|
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"vocab_size": 32,
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"xvector_output_dim": 512
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}
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results/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6632eb608edacf1e3977b987719741db6567b25d68d7e94a698090c1a05e4ca0
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size 378302360
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results/preprocessor_config.json
ADDED
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{
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"do_normalize": true,
|
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
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"feature_size": 1,
|
5 |
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"padding_side": "right",
|
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"padding_value": 0.0,
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"processor_class": "Wav2Vec2Processor",
|
8 |
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"return_attention_mask": false,
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"sampling_rate": 16000
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}
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results/special_tokens_map.json
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{
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"bos_token": "<s>",
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"eos_token": "</s>",
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"pad_token": "<pad>",
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"unk_token": "<unk>"
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}
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results/tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
|
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"content": "<pad>",
|
5 |
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"lstrip": true,
|
6 |
+
"normalized": false,
|
7 |
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"rstrip": true,
|
8 |
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"single_word": false,
|
9 |
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"special": false
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},
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"1": {
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"content": "<s>",
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"lstrip": true,
|
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"normalized": false,
|
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"rstrip": true,
|
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"single_word": false,
|
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+
"special": false
|
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+
},
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"2": {
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"content": "</s>",
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"lstrip": true,
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"normalized": false,
|
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"rstrip": true,
|
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"single_word": false,
|
25 |
+
"special": false
|
26 |
+
},
|
27 |
+
"3": {
|
28 |
+
"content": "<unk>",
|
29 |
+
"lstrip": true,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": true,
|
32 |
+
"single_word": false,
|
33 |
+
"special": false
|
34 |
+
}
|
35 |
+
},
|
36 |
+
"bos_token": "<s>",
|
37 |
+
"clean_up_tokenization_spaces": true,
|
38 |
+
"do_lower_case": false,
|
39 |
+
"do_normalize": true,
|
40 |
+
"eos_token": "</s>",
|
41 |
+
"model_max_length": 1000000000000000019884624838656,
|
42 |
+
"pad_token": "<pad>",
|
43 |
+
"processor_class": "Wav2Vec2Processor",
|
44 |
+
"replace_word_delimiter_char": " ",
|
45 |
+
"return_attention_mask": false,
|
46 |
+
"target_lang": null,
|
47 |
+
"tokenizer_class": "Wav2Vec2CTCTokenizer",
|
48 |
+
"unk_token": "<unk>",
|
49 |
+
"word_delimiter_token": "|"
|
50 |
+
}
|
results/vocab.json
ADDED
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"'": 27,
|
3 |
+
"</s>": 2,
|
4 |
+
"<pad>": 0,
|
5 |
+
"<s>": 1,
|
6 |
+
"<unk>": 3,
|
7 |
+
"A": 7,
|
8 |
+
"B": 24,
|
9 |
+
"C": 19,
|
10 |
+
"D": 14,
|
11 |
+
"E": 5,
|
12 |
+
"F": 20,
|
13 |
+
"G": 21,
|
14 |
+
"H": 11,
|
15 |
+
"I": 10,
|
16 |
+
"J": 29,
|
17 |
+
"K": 26,
|
18 |
+
"L": 15,
|
19 |
+
"M": 17,
|
20 |
+
"N": 9,
|
21 |
+
"O": 8,
|
22 |
+
"P": 23,
|
23 |
+
"Q": 30,
|
24 |
+
"R": 13,
|
25 |
+
"S": 12,
|
26 |
+
"T": 6,
|
27 |
+
"U": 16,
|
28 |
+
"V": 25,
|
29 |
+
"W": 18,
|
30 |
+
"X": 28,
|
31 |
+
"Y": 22,
|
32 |
+
"Z": 31,
|
33 |
+
"|": 4
|
34 |
+
}
|