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End of training

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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: elgeish/wav2vec2-large-xlsr-53-arabic
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: result
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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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+ # result
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+
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+ This model is a fine-tuned version of [elgeish/wav2vec2-large-xlsr-53-arabic](https://huggingface.co/elgeish/wav2vec2-large-xlsr-53-arabic) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5629
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+ - Wer: 0.5924
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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: 0.001
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+ - train_batch_size: 4
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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: 1000
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+ - num_epochs: 10
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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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+ | 8.2289 | 2.0 | 500 | 1.8545 | 0.9936 |
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+ | 1.2421 | 4.0 | 1000 | 1.5310 | 0.9443 |
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+ | 1.0752 | 6.0 | 1500 | 1.3956 | 0.9045 |
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+ | 0.6889 | 8.0 | 2000 | 0.7714 | 0.6768 |
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+ | 0.3904 | 10.0 | 2500 | 0.5629 | 0.5924 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 2.4.0
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
config.json ADDED
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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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+ "model_type": "wav2vec2",
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+ "num_adapter_layers": 3,
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+ "num_codevector_groups": 2,
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+ "num_codevectors_per_group": 320,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.45.2",
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+ "use_weighted_layer_sum": false,
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+ "vocab_size": 39,
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+ "xvector_output_dim": 512
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+ }
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