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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: facebook/wav2vec2-large-960h
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - gigaspeech
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec_best
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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: gigaspeech
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+ type: gigaspeech
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+ config: xs
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+ split: validation
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+ args: xs
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.2950402352212937
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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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+ # wav2vec_best
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-960h](https://huggingface.co/facebook/wav2vec2-large-960h) on the gigaspeech dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7597
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+ - Wer: 0.2950
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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: 5e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 8
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 200
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+ - num_epochs: 3
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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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+ | 1.5437 | 1.0 | 1174 | 0.7964 | 0.3166 |
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+ | 1.4351 | 2.0 | 2348 | 0.7771 | 0.3061 |
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+ | 0.6393 | 2.9978 | 3519 | 0.7597 | 0.2950 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.50.3
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.5.0
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+ - Tokenizers 0.21.1
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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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+ "model_type": "wav2vec2",
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