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README.md ADDED
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+ ---
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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: w2v2-bert-ft-btb-cy
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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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+ # w2v2-bert-ft-btb-cy
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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: 2.9375
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+ - Wer: 1.0
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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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+ - training_steps: 2500
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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 | 0.1414 | 100 | 6.9702 | 1.0 |
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+ | No log | 0.2829 | 200 | 3.3676 | 1.0 |
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+ | No log | 0.4243 | 300 | 3.0393 | 1.0 |
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+ | No log | 0.5658 | 400 | 2.9887 | 1.0 |
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+ | 4.717 | 0.7072 | 500 | 3.0227 | 1.0 |
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+ | 4.717 | 0.8487 | 600 | 3.0406 | 1.0 |
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+ | 4.717 | 0.9901 | 700 | 3.0029 | 1.0 |
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+ | 4.717 | 1.1315 | 800 | 2.9483 | 1.0 |
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+ | 4.717 | 1.2730 | 900 | 2.9511 | 1.0 |
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+ | 3.0065 | 1.4144 | 1000 | 2.9473 | 1.0 |
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+ | 3.0065 | 1.5559 | 1100 | 2.9448 | 1.0 |
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+ | 3.0065 | 1.6973 | 1200 | 2.9470 | 1.0 |
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+ | 3.0065 | 1.8388 | 1300 | 2.9446 | 1.0 |
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+ | 3.0065 | 1.9802 | 1400 | 2.9432 | 1.0 |
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+ | 2.9634 | 2.1216 | 1500 | 2.9476 | 1.0 |
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+ | 2.9634 | 2.2631 | 1600 | 2.9624 | 1.0 |
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+ | 2.9634 | 2.4045 | 1700 | 2.9581 | 1.0 |
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+ | 2.9634 | 2.5460 | 1800 | 2.9553 | 1.0 |
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+ | 2.9634 | 2.6874 | 1900 | 2.9515 | 1.0 |
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+ | 2.9677 | 2.8289 | 2000 | 2.9481 | 1.0 |
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+ | 2.9677 | 2.9703 | 2100 | 2.9509 | 1.0 |
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+ | 2.9677 | 3.1117 | 2200 | 2.9408 | 1.0 |
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+ | 2.9677 | 3.2532 | 2300 | 2.9393 | 1.0 |
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+ | 2.9677 | 3.3946 | 2400 | 2.9381 | 1.0 |
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+ | 2.9612 | 3.5361 | 2500 | 2.9375 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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