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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-nc-4.0
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+ base_model: facebook/mms-1b-all
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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: mms-1b-bigcgen-female-20hrs-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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+ # mms-1b-bigcgen-female-20hrs-model
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+
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+ This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: inf
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+ - Wer: 0.5260
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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: 4
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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: Use 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: 100
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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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+ | 13.9528 | 0.0752 | 100 | inf | 1.0431 |
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+ | 6.1846 | 0.1505 | 200 | inf | 1.0030 |
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+ | 5.4651 | 0.2257 | 300 | inf | 1.0386 |
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+ | 4.4356 | 0.3010 | 400 | inf | 0.8831 |
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+ | 2.2016 | 0.3762 | 500 | inf | 0.6218 |
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+ | 1.8013 | 0.4515 | 600 | inf | 0.5746 |
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+ | 1.7499 | 0.5267 | 700 | inf | 0.5793 |
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+ | 1.6979 | 0.6020 | 800 | inf | 0.5501 |
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+ | 1.5567 | 0.6772 | 900 | inf | 0.5439 |
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+ | 1.6301 | 0.7524 | 1000 | inf | 0.5355 |
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+ | 1.6362 | 0.8277 | 1100 | inf | 0.5367 |
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+ | 1.5247 | 0.9029 | 1200 | inf | 0.5326 |
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+ | 1.4012 | 0.9782 | 1300 | inf | 0.5346 |
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+ | 1.6397 | 1.0534 | 1400 | inf | 0.5301 |
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+ | 1.5258 | 1.1287 | 1500 | inf | 0.5285 |
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+ | 1.4144 | 1.2039 | 1600 | inf | 0.5244 |
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+ | 1.4363 | 1.2792 | 1700 | inf | 0.5144 |
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+ | 1.3733 | 1.3544 | 1800 | inf | 0.5358 |
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+ | 1.4592 | 1.4296 | 1900 | inf | 0.5598 |
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+ | 1.3499 | 1.5049 | 2000 | inf | 0.5192 |
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+ | 1.4039 | 1.5801 | 2100 | inf | 0.5228 |
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+ | 1.4057 | 1.6554 | 2200 | inf | 0.5289 |
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+ | 1.4961 | 1.7306 | 2300 | inf | 0.5323 |
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+ | 1.3975 | 1.8059 | 2400 | inf | 0.5119 |
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+ | 1.4725 | 1.8811 | 2500 | inf | 0.5260 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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