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xls-r-1b-bem-genbed-f-model

Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
genbed
Generated from Trainer
Inference Endpoints
Model card Files Community
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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-xls-r-1b
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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: xls-r-1b-bem-genbed-f-model
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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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+ # xls-r-1b-bem-genbed-f-model
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3247
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+ - Wer: 0.5988
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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: 4
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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: 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: 500
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+ - num_epochs: 30.0
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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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+ | No log | 0.2740 | 100 | 3.0378 | 1.0 |
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+ | No log | 0.5479 | 200 | 0.8302 | 0.9818 |
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+ | No log | 0.8219 | 300 | 0.6783 | 0.9103 |
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+ | No log | 1.0959 | 400 | 0.5512 | 0.8721 |
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+ | 1.8782 | 1.3699 | 500 | 0.5296 | 0.8568 |
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+ | 1.8782 | 1.6438 | 600 | 0.4413 | 0.7333 |
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+ | 1.8782 | 1.9178 | 700 | 0.4747 | 0.7614 |
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+ | 1.8782 | 2.1918 | 800 | 0.3884 | 0.6667 |
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+ | 1.8782 | 2.4658 | 900 | 0.3577 | 0.6355 |
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+ | 0.5114 | 2.7397 | 1000 | 0.3585 | 0.6321 |
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+ | 0.5114 | 3.0137 | 1100 | 0.3641 | 0.6607 |
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+ | 0.5114 | 3.2877 | 1200 | 0.3813 | 0.7282 |
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+ | 0.5114 | 3.5616 | 1300 | 0.3829 | 0.7086 |
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+ | 0.5114 | 3.8356 | 1400 | 0.3682 | 0.6413 |
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+ | 0.3931 | 4.1096 | 1500 | 0.3527 | 0.6221 |
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+ | 0.3931 | 4.3836 | 1600 | 0.3481 | 0.6297 |
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+ | 0.3931 | 4.6575 | 1700 | 0.3541 | 0.6193 |
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+ | 0.3931 | 4.9315 | 1800 | 0.3355 | 0.6242 |
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+ | 0.3931 | 5.2055 | 1900 | 0.3339 | 0.5801 |
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+ | 0.3293 | 5.4795 | 2000 | 0.3137 | 0.5529 |
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+ | 0.3293 | 5.7534 | 2100 | 0.3132 | 0.5822 |
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+ | 0.3293 | 6.0274 | 2200 | 0.3145 | 0.5676 |
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+ | 0.3293 | 6.3014 | 2300 | 0.3283 | 0.5961 |
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+ | 0.3293 | 6.5753 | 2400 | 0.3247 | 0.5988 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.0.dev0
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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