Jhon Parra commited on
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guarani files from personal repo

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ - robust-speech-event
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+ datasets:
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+ - common_voice
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+ model-index:
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+ - name: wav2vec2-large-xls-r-300m-guarani-small
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # wav2vec2-large-xls-r-300m-guarani-small
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4964
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+ - Wer: 0.5957
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 30
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 6.65 | 100 | 1.1326 | 1.0 |
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+ | 1.6569 | 13.32 | 200 | 0.5264 | 0.6478 |
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+ | 1.6569 | 19.97 | 300 | 0.5370 | 0.6261 |
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+ | 0.2293 | 26.65 | 400 | 0.4964 | 0.5957 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.16.2
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.18.3
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+ - Tokenizers 0.11.0
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+ {
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+ "_name_or_path": "facebook/wav2vec2-xls-r-300m",
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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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+ "Wav2Vec2ForCTC"
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+ ],
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+ "attention_dropout": 0.0,
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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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+ 512,
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+ "ctc_loss_reduction": "mean",
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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": 0.0,
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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": 0.0,
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+ "hidden_size": 1024,
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+ "initializer_range": 0.02,
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+ "layer_norm_eps": 1e-05,
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+ "layerdrop": 0.0,
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+ "mask_feature_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": 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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+ "torch_dtype": "float32",
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+ "transformers_version": "4.16.2",
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+ "use_weighted_layer_sum": false,
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+ "vocab_size": 46,
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+ "xvector_output_dim": 512
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+ }
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