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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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+ language:
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+ - en
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-large-xlsr-53
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - arielcerdap/TimeStamped
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Wav2Vec2 TimeStamped Stutter - Ariel Cerda
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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: TimeStamped
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+ type: arielcerdap/TimeStamped
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+ args: 'config: en, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.9991797676008203
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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 TimeStamped Stutter - Ariel Cerda
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the TimeStamped dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: nan
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+ - Wer: 0.9992
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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: 0.0003
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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: 500
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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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+ | 11.5515 | 1.1696 | 100 | 11.9112 | 1.0001 |
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+ | 13.4395 | 2.3392 | 200 | 11.9112 | 1.0001 |
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+ | 11.9169 | 3.5088 | 300 | 11.9112 | 1.0001 |
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+ | 11.1801 | 4.6784 | 400 | 11.9112 | 1.0001 |
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+ | 15.3393 | 5.8480 | 500 | 11.9112 | 1.0001 |
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+ | 11.8177 | 7.0175 | 600 | 11.9112 | 1.0001 |
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+ | 10.7941 | 8.1871 | 700 | 11.9112 | 1.0001 |
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+ | 13.8075 | 9.3567 | 800 | 11.9112 | 1.0001 |
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+ | 11.5275 | 10.5263 | 900 | 11.9112 | 1.0001 |
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+ | 10.1228 | 11.6959 | 1000 | 11.9112 | 1.0001 |
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+ | 13.7071 | 12.8655 | 1100 | 11.9112 | 1.0001 |
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+ | 11.6933 | 14.0351 | 1200 | 11.9112 | 1.0001 |
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+ | 10.885 | 15.2047 | 1300 | 11.9112 | 1.0001 |
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+ | 14.2349 | 16.3743 | 1400 | 11.9112 | 1.0001 |
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+ | 12.8886 | 17.5439 | 1500 | 11.9112 | 1.0001 |
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+ | 0.0 | 18.7135 | 1600 | nan | 0.9992 |
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+ | 0.0 | 19.8830 | 1700 | nan | 0.9992 |
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+ | 0.0 | 21.0526 | 1800 | nan | 0.9992 |
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+ | 0.0 | 22.2222 | 1900 | nan | 0.9992 |
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+ | 0.0 | 23.3918 | 2000 | nan | 0.9992 |
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+ | 0.0 | 24.5614 | 2100 | nan | 0.9992 |
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+ | 0.0 | 25.7310 | 2200 | nan | 0.9992 |
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+ | 0.0 | 26.9006 | 2300 | nan | 0.9992 |
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+ | 0.0 | 28.0702 | 2400 | nan | 0.9992 |
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+ | 0.0 | 29.2398 | 2500 | nan | 0.9992 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.19.1
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