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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: facebook/w2v-bert-2.0
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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: w2v-bert-bem-genbed-m-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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+ # w2v-bert-bem-genbed-m-model
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+
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+ This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4253
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+ - Wer: 0.5296
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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: 8
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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: 16
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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: 100
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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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+ | 0.7215 | 1.1019 | 200 | 0.6150 | 0.7430 |
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+ | 0.5519 | 2.2039 | 400 | 0.5605 | 0.7116 |
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+ | 0.4346 | 3.3058 | 600 | 0.4709 | 0.6378 |
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+ | 0.3545 | 4.4077 | 800 | 0.4686 | 0.5984 |
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+ | 0.3004 | 5.5096 | 1000 | 0.4578 | 0.6203 |
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+ | 0.2498 | 6.6116 | 1200 | 0.4245 | 0.5246 |
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+ | 0.23 | 7.7135 | 1400 | 0.4168 | 0.5478 |
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+ | 0.1959 | 8.8154 | 1600 | 0.4212 | 0.5230 |
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+ | 0.1682 | 9.9174 | 1800 | 0.4357 | 0.5054 |
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+ | 0.1459 | 11.0193 | 2000 | 0.4253 | 0.5296 |
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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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