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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-combined-25hrs-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-combined-25hrs-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: 0.5155
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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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+ | 14.5485 | 0.0611 | 100 | inf | 1.0039 |
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+ | 6.1502 | 0.1222 | 200 | inf | 1.0675 |
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+ | 5.1685 | 0.1833 | 300 | inf | 1.0053 |
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+ | 2.0876 | 0.2443 | 400 | inf | 0.5857 |
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+ | 1.7116 | 0.3054 | 500 | inf | 0.5759 |
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+ | 1.6505 | 0.3665 | 600 | inf | 0.5579 |
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+ | 1.6573 | 0.4276 | 700 | inf | 0.5471 |
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+ | 1.4679 | 0.4887 | 800 | inf | 0.5528 |
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+ | 1.4955 | 0.5498 | 900 | inf | 0.5369 |
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+ | 1.664 | 0.6109 | 1000 | inf | 0.5328 |
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+ | 1.61 | 0.6720 | 1100 | inf | 0.5335 |
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+ | 1.6414 | 0.7330 | 1200 | inf | 0.5293 |
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+ | 1.6321 | 0.7941 | 1300 | inf | 0.5271 |
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+ | 1.4686 | 0.8552 | 1400 | inf | 0.5297 |
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+ | 1.5073 | 0.9163 | 1500 | inf | 0.5326 |
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+ | 1.6164 | 0.9774 | 1600 | inf | 0.5235 |
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+ | 1.577 | 1.0385 | 1700 | inf | 0.5238 |
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+ | 1.383 | 1.0996 | 1800 | inf | 0.5217 |
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+ | 1.4391 | 1.1607 | 1900 | inf | 0.5292 |
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+ | 1.5327 | 1.2217 | 2000 | inf | 0.5255 |
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+ | 1.3653 | 1.2828 | 2100 | inf | 0.5195 |
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+ | 1.4901 | 1.3439 | 2200 | inf | 0.5187 |
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+ | 1.4263 | 1.4050 | 2300 | inf | 0.5169 |
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+ | 1.4603 | 1.4661 | 2400 | inf | 0.5179 |
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+ | 1.4802 | 1.5272 | 2500 | inf | 0.5155 |
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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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