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README.md ADDED
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+ ---
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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-bem-female-sv
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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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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/cicasote/huggingface/runs/tuxgh6td)
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+ # mms-1b-bem-female-sv
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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: 0.2132
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+ - Wer: 0.3557
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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: 0.001
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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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+ - 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: 5.0
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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 | 0.3992 | 200 | 0.3566 | 0.5019 |
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+ | No log | 0.7984 | 400 | 0.2620 | 0.4029 |
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+ | 1.7214 | 1.1976 | 600 | 0.2546 | 0.4100 |
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+ | 1.7214 | 1.5968 | 800 | 0.2359 | 0.3965 |
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+ | 0.2801 | 1.9960 | 1000 | 0.2322 | 0.3810 |
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+ | 0.2801 | 2.3952 | 1200 | 0.2305 | 0.3746 |
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+ | 0.2801 | 2.7944 | 1400 | 0.2258 | 0.3336 |
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+ | 0.2528 | 3.1936 | 1600 | 0.2262 | 0.4309 |
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+ | 0.2528 | 3.5928 | 1800 | 0.2164 | 0.3514 |
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+ | 0.2351 | 3.9920 | 2000 | 0.2215 | 0.3894 |
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+ | 0.2351 | 4.3912 | 2200 | 0.2165 | 0.3624 |
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+ | 0.2351 | 4.7904 | 2400 | 0.2132 | 0.3557 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.43.0
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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