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csikasote
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mms-1b-nyagen-male-model

Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
nyagen
mms
Generated from Trainer
Inference Endpoints
Model card Files Community
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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-nyagen-male-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-nyagen-male-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: 0.1298
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+ - Wer: 0.1952
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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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+ - 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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+ - 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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+ | 6.345 | 0.2463 | 100 | 0.4506 | 0.4026 |
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+ | 0.353 | 0.4926 | 200 | 0.2066 | 0.2924 |
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+ | 0.2989 | 0.7389 | 300 | 0.1829 | 0.2715 |
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+ | 0.2402 | 0.9852 | 400 | 0.1674 | 0.2546 |
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+ | 0.2302 | 1.2315 | 500 | 0.1582 | 0.2436 |
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+ | 0.2279 | 1.4778 | 600 | 0.1602 | 0.2428 |
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+ | 0.2264 | 1.7241 | 700 | 0.1507 | 0.2287 |
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+ | 0.2276 | 1.9704 | 800 | 0.1496 | 0.2353 |
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+ | 0.2088 | 2.2167 | 900 | 0.1460 | 0.2208 |
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+ | 0.1881 | 2.4631 | 1000 | 0.1455 | 0.2165 |
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+ | 0.2079 | 2.7094 | 1100 | 0.1418 | 0.2168 |
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+ | 0.196 | 2.9557 | 1200 | 0.1404 | 0.2086 |
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+ | 0.1782 | 3.2020 | 1300 | 0.1373 | 0.2078 |
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+ | 0.1741 | 3.4483 | 1400 | 0.1343 | 0.1944 |
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+ | 0.1948 | 3.6946 | 1500 | 0.1318 | 0.2137 |
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+ | 0.1904 | 3.9409 | 1600 | 0.1307 | 0.2043 |
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+ | 0.1762 | 4.1872 | 1700 | 0.1313 | 0.2003 |
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+ | 0.1718 | 4.4335 | 1800 | 0.1275 | 0.1932 |
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+ | 0.1595 | 4.6798 | 1900 | 0.1276 | 0.1952 |
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+ | 0.1811 | 4.9261 | 2000 | 0.1290 | 0.1983 |
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+ | 0.1477 | 5.1724 | 2100 | 0.1298 | 0.1952 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.0.dev0
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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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