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--- |
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license: apache-2.0 |
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base_model: facebook/hubert-large-ll60k |
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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: HuBERT_Jibbali_lang |
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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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# HuBERT_Jibbali_lang |
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This model is a fine-tuned version of [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2017 |
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- Wer: 0.1944 |
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- Cet: 0.1189 |
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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: 0.0003 |
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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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- gradient_accumulation_steps: 2 |
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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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- num_epochs: 20 |
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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 | Cet | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 10.6563 | 0.99 | 56 | 5.6577 | 1.0 | 0.9812 | |
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| 3.3895 | 2.0 | 113 | 3.2018 | 1.0 | 0.9812 | |
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| 3.1588 | 2.99 | 169 | 3.1347 | 1.0 | 0.9812 | |
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| 3.1308 | 4.0 | 226 | 3.0567 | 1.0 | 0.9812 | |
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| 2.8933 | 4.99 | 282 | 2.8226 | 1.0 | 0.9353 | |
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| 2.5444 | 6.0 | 339 | 2.0947 | 1.0 | 0.8588 | |
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| 0.995 | 6.99 | 395 | 0.5049 | 0.4974 | 0.1654 | |
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| 0.3567 | 8.0 | 452 | 0.2622 | 0.2485 | 0.1132 | |
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| 0.2914 | 8.99 | 508 | 0.1980 | 0.2105 | 0.0749 | |
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| 0.14 | 10.0 | 565 | 0.2154 | 0.2069 | 0.0821 | |
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| 0.1442 | 10.99 | 621 | 0.1965 | 0.1988 | 0.0969 | |
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| 0.1401 | 12.0 | 678 | 0.2135 | 0.1937 | 0.0960 | |
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| 0.1019 | 12.99 | 734 | 0.2185 | 0.1948 | 0.1094 | |
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| 0.1088 | 14.0 | 791 | 0.1957 | 0.1966 | 0.1121 | |
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| 0.1314 | 14.99 | 847 | 0.1983 | 0.1933 | 0.1019 | |
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| 0.0522 | 16.0 | 904 | 0.2026 | 0.1944 | 0.1258 | |
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| 0.126 | 16.99 | 960 | 0.2033 | 0.1944 | 0.1142 | |
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| 0.1028 | 18.0 | 1017 | 0.1940 | 0.1974 | 0.1158 | |
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| 0.0767 | 18.99 | 1073 | 0.1969 | 0.1948 | 0.1149 | |
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| 0.0468 | 19.82 | 1120 | 0.2017 | 0.1944 | 0.1189 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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