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  1. README.md +26 -0
  2. config.json +115 -0
  3. pytorch_model.bin +3 -0
README.md ADDED
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+ ---
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+ language: el
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+ tags:
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+ - audio
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+ - automatic-speech-recognition
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+ - voxpopuli-v2
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+ datasets:
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+ - voxpopuli
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+ license: cc-by-nc-4.0
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+ inference: false
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+ ---
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+
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+ # Wav2Vec2-large-VoxPopuli-V2
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+
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+ [Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) large model pretrained only in **el** on **17.7** unlabeled datat of the [VoxPopuli corpus](https://arxiv.org/abs/2101.00390).
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+
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+ The model is pretrained on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz.
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+
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+ **Note**: This model does not have a tokenizer as it was pretrained on audio alone. In order to use this model for **speech recognition**, a tokenizer should be created and the model should be fine-tuned on labeled text data in **el**. Check out [this blog](https://huggingface.co/blog/fine-tune-xlsr-wav2vec2) for a more in-detail explanation of how to fine-tune the model.
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+
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+ **Paper**: *[VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation
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+ Learning, Semi-Supervised Learning and Interpretation](https://arxiv.org/abs/2101.00390)*
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+
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+ **Authors**: *Changhan Wang, Morgane Riviere, Ann Lee, Anne Wu, Chaitanya Talnikar, Daniel Haziza, Mary Williamson, Juan Pino, Emmanuel Dupoux* from *Facebook AI*.
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+
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+ See the official website for more information, [here](https://github.com/facebookresearch/voxpopuli/).
config.json ADDED
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+ {
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+ "activation_dropout": 0.0,
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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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+ "Wav2Vec2ForPreTraining"
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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": 768,
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+ "contrastive_logits_temperature": 0.1,
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+ "conv_bias": true,
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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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+ ],
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+ "conv_kernel": [
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+ "conv_stride": [
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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": true,
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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": "layer",
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+ "feat_proj_dropout": 0.1,
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+ "feat_quantizer_dropout": 0.0,
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+ "final_dropout": 0.0,
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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_size": 1024,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "layer_norm_eps": 1e-05,
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+ "layerdrop": 0.1,
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+ "mask_channel_length": 10,
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+ "mask_channel_min_space": 1,
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+ "mask_channel_other": 0.0,
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+ "mask_channel_prob": 0.0,
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+ "mask_channel_selection": "static",
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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_other": 0.0,
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+ "mask_time_prob": 0.075,
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+ "mask_time_selection": "static",
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+ "model_type": "wav2vec2",
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+ "num_adapter_layers": 3,
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+ "num_attention_heads": 16,
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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": 24,
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+ "num_negatives": 100,
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+ "output_hidden_size": 1024,
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+ "pad_token_id": 0,
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+ "proj_codevector_dim": 768,
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+ "tdnn_dilation": [
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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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+ 1500
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+ ],
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+ "tdnn_kernel": [
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+ 5,
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.17.0.dev0",
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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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