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zarakun/wav2vec

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - speech_commands
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+ model-index:
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+ - name: tmp
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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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+ # tmp
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the speech_commands dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 0.5422
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+ - eval_accuracy: 0.8916
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+ - eval_f1: 0.8835
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+ - eval_runtime: 7.8567
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+ - eval_samples_per_second: 392.147
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+ - eval_steps_per_second: 1.655
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+ - epoch: 4.0423
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+ - step: 861
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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: 3e-05
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+ - train_batch_size: 240
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+ - eval_batch_size: 240
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+ - seed: 42
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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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+ - num_epochs: 100
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
config.json ADDED
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+ {
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+ "_name_or_path": "facebook/wav2vec2-base",
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+ "activation_dropout": 0.0,
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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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+ "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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+ "vocab_size": 32,
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