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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: wav2vec2-large-mms-1b-kazakh-speech2ner-ksc_t-16b-4ep |
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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-kazakh-speech2ner-ksc_t-16b-4ep |
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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: 0.2397 |
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- Wer: 0.3099 |
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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: 1e-05 |
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- train_batch_size: 16 |
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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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- 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: 1000 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.3934 | 0.22 | 2000 | 0.3610 | 0.3687 | |
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| 0.3361 | 0.43 | 4000 | 0.2983 | 0.3412 | |
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| 0.3211 | 0.65 | 6000 | 0.2779 | 0.3300 | |
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| 0.3146 | 0.87 | 8000 | 0.2685 | 0.3238 | |
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| 0.3104 | 1.09 | 10000 | 0.2613 | 0.3210 | |
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| 0.2965 | 1.3 | 12000 | 0.2571 | 0.3188 | |
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| 0.3004 | 1.52 | 14000 | 0.2531 | 0.3166 | |
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| 0.2889 | 1.74 | 16000 | 0.2504 | 0.3153 | |
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| 0.2955 | 1.96 | 18000 | 0.2476 | 0.3138 | |
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| 0.2869 | 2.17 | 20000 | 0.2465 | 0.3126 | |
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| 0.2855 | 2.39 | 22000 | 0.2443 | 0.3117 | |
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| 0.2927 | 2.61 | 24000 | 0.2431 | 0.3111 | |
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| 0.2789 | 2.83 | 26000 | 0.2421 | 0.3107 | |
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| 0.2854 | 3.04 | 28000 | 0.2412 | 0.3105 | |
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| 0.2918 | 3.26 | 30000 | 0.2404 | 0.3099 | |
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| 0.2768 | 3.48 | 32000 | 0.2401 | 0.3096 | |
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| 0.2771 | 3.69 | 34000 | 0.2398 | 0.3099 | |
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| 0.2733 | 3.91 | 36000 | 0.2397 | 0.3099 | |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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