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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- generated_from_trainer |
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base_model: facebook/mms-1b-all |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-mms-1b-livvi-karelian-CodeSwitching |
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results: [] |
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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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# wav2vec2-large-mms-1b-livvi-karelian-CodeSwitching |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3113 |
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- Wer: 0.4087 |
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- Cer: 0.0910 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0005 |
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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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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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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- training_steps: 10000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:| |
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| 1.4219 | 4.5351 | 500 | 0.4570 | 0.5677 | 0.1335 | |
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| 0.5951 | 9.0703 | 1000 | 0.4008 | 0.5142 | 0.1186 | |
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| 0.5314 | 13.6054 | 1500 | 0.3725 | 0.4942 | 0.1126 | |
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| 0.4916 | 18.1406 | 2000 | 0.3626 | 0.4692 | 0.1067 | |
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| 0.4563 | 22.6757 | 2500 | 0.3465 | 0.4540 | 0.1035 | |
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| 0.4331 | 27.2109 | 3000 | 0.3310 | 0.4455 | 0.1010 | |
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| 0.4129 | 31.7460 | 3500 | 0.3283 | 0.4516 | 0.1019 | |
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| 0.394 | 36.2812 | 4000 | 0.3289 | 0.4482 | 0.0994 | |
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| 0.3715 | 40.8163 | 4500 | 0.3203 | 0.4374 | 0.0985 | |
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| 0.3646 | 45.3515 | 5000 | 0.3109 | 0.4327 | 0.0966 | |
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| 0.3508 | 49.8866 | 5500 | 0.3136 | 0.4276 | 0.0958 | |
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| 0.3376 | 54.4218 | 6000 | 0.3198 | 0.4246 | 0.0950 | |
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| 0.3283 | 58.9569 | 6500 | 0.3203 | 0.4232 | 0.0943 | |
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| 0.3222 | 63.4921 | 7000 | 0.3126 | 0.4134 | 0.0932 | |
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| 0.3104 | 68.0272 | 7500 | 0.3140 | 0.4168 | 0.0933 | |
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| 0.3026 | 72.5624 | 8000 | 0.3136 | 0.4110 | 0.0920 | |
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| 0.3003 | 77.0975 | 8500 | 0.3137 | 0.4175 | 0.0926 | |
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| 0.2896 | 81.6327 | 9000 | 0.3150 | 0.4107 | 0.0912 | |
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| 0.2885 | 86.1678 | 9500 | 0.3110 | 0.4090 | 0.0914 | |
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| 0.2869 | 90.7029 | 10000 | 0.3113 | 0.4087 | 0.0910 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.2 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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