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muratsimsek003/wav2vec2-base-turkish

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README.md ADDED
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+ ---
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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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+ - common_voice_6_1
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-base-turkish-istech
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: common_voice_6_1
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+ type: common_voice_6_1
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+ config: tr
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+ split: train[:10%]
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+ args: tr
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 1.0105162523900573
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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-base-turkish-istech
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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 common_voice_6_1 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 17.9554
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+ - Wer: 1.0105
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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: 0.0001
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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: 20
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+ - num_epochs: 0.5
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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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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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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+ "Wav2Vec2ForCTC"
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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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+ ],
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+ "conv_kernel": [
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+ "ctc_loss_reduction": "mean",
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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_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": 0.0,
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+ "freeze_feat_extract_train": true,
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+ "initializer_range": 0.02,
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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_other": 0.0,
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+ "mask_time_prob": 0.05,
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+ "mask_time_selection": "static",
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+ "model_type": "wav2vec2",
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+ "no_mask_channel_overlap": false,
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+ "no_mask_time_overlap": false,
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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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+ "tdnn_dim": [
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+ "tdnn_kernel": [
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.4",
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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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