ctaguchi
/

ssc-tob-mms-model

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 ---
 library_name: transformers
-tags: []
 ---
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 ---
 library_name: transformers
+license: cc-by-nc-4.0
+base_model: facebook/mms-1b-all
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: ssc-tob-mms-model
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# ssc-tob-mms-model
+This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2153
+- Cer: 0.2848
+- Wer: 0.9304
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0003
+- train_batch_size: 8
+- eval_batch_size: 12
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss | Cer    | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
+| 2.4972        | 0.3630 | 200  | 1.0789          | 0.2723 | 0.8209 |
+| 1.309         | 0.7260 | 400  | 0.8159          | 0.1907 | 0.6379 |
+| 1.0714        | 1.0889 | 600  | 0.7904          | 0.1860 | 0.6143 |
+| 1.0315        | 1.4519 | 800  | 0.7554          | 0.1801 | 0.6027 |
+| 1.0204        | 1.8149 | 1000 | 0.7355          | 0.1782 | 0.5966 |
+| 0.9409        | 2.1779 | 1200 | 0.7301          | 0.1781 | 0.5891 |
+| 0.9373        | 2.5408 | 1400 | 0.7385          | 0.1768 | 0.5841 |
+| 0.9476        | 2.9038 | 1600 | 0.7390          | 0.1752 | 0.5821 |
+| 0.95          | 3.2668 | 1800 | 0.7275          | 0.1746 | 0.5768 |
+| 0.9217        | 3.6298 | 2000 | 0.7504          | 0.1793 | 0.5886 |
+| 0.9129        | 3.9927 | 2200 | 0.7343          | 0.1788 | 0.5883 |
+| 0.9241        | 4.3557 | 2400 | 0.7354          | 0.1781 | 0.5878 |
+| 0.9233        | 4.7187 | 2600 | 0.7380          | 0.1726 | 0.5739 |
+| 0.9115        | 5.0817 | 2800 | 0.7470          | 0.1822 | 0.6151 |
+| 0.8821        | 5.4446 | 3000 | 0.7608          | 0.1822 | 0.6040 |
+| 0.9528        | 5.8076 | 3200 | 0.8443          | 0.2133 | 0.7036 |
+| 0.9555        | 6.1706 | 3400 | 0.8208          | 0.2072 | 0.6673 |
+| 0.984         | 6.5336 | 3600 | 0.8248          | 0.1927 | 0.6297 |
+| 1.0761        | 6.8966 | 3800 | 0.9289          | 0.2588 | 0.8101 |
+| 1.2933        | 7.2595 | 4000 | 1.1071          | 0.2959 | 0.8936 |
+| 1.3775        | 7.6225 | 4200 | 1.2098          | 0.4531 | 0.9980 |
+| 1.4115        | 7.9855 | 4400 | 1.2473          | 0.4800 | 0.9957 |
+| 1.3867        | 8.3485 | 4600 | 1.1974          | 0.3281 | 0.9329 |
+| 1.409         | 8.7114 | 4800 | 1.2375          | 0.2467 | 0.8110 |
+| 1.3689        | 9.0744 | 5000 | 1.2202          | 0.2413 | 0.8018 |
+| 1.3787        | 9.4374 | 5200 | 1.2229          | 0.2721 | 0.9040 |
+| 1.373         | 9.8004 | 5400 | 1.2153          | 0.2848 | 0.9304 |
+### Framework versions
+- Transformers 4.57.2
+- Pytorch 2.9.1+cu128
+- Datasets 3.6.0
+- Tokenizers 0.22.0

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