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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: Osiris_asr_model |
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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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# Osiris_asr_model |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0600 |
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- Wer: 1.0 |
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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: 10 |
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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: 20 |
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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: 50 |
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- training_steps: 1000 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 45.8209 | 50.0 | 50 | 21.0347 | 1.0182 | |
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| 10.2898 | 100.0 | 100 | 5.1552 | 1.0 | |
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| 5.7188 | 150.0 | 150 | 4.9140 | 1.0 | |
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| 5.3358 | 200.0 | 200 | 4.7650 | 1.0 | |
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| 5.1381 | 250.0 | 250 | 4.6797 | 1.0 | |
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| 4.9841 | 300.0 | 300 | 4.6168 | 1.0 | |
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| 4.9255 | 350.0 | 350 | 4.5741 | 1.0 | |
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| 4.8353 | 400.0 | 400 | 4.5321 | 1.0 | |
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| 4.7704 | 450.0 | 450 | 4.5100 | 1.0 | |
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| 4.6257 | 500.0 | 500 | 3.9382 | 1.0 | |
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| 3.8106 | 550.0 | 550 | 3.3939 | 1.0 | |
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| 3.5095 | 600.0 | 600 | 3.2887 | 1.0 | |
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| 3.3716 | 650.0 | 650 | 3.1967 | 1.0 | |
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| 3.3025 | 700.0 | 700 | 3.1539 | 1.0 | |
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| 3.2532 | 750.0 | 750 | 3.1477 | 1.0 | |
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| 3.2086 | 800.0 | 800 | 3.0984 | 1.0 | |
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| 3.1889 | 850.0 | 850 | 3.0857 | 1.0 | |
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| 3.162 | 900.0 | 900 | 3.0819 | 1.0 | |
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| 3.1411 | 950.0 | 950 | 3.0610 | 1.0 | |
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| 3.1397 | 1000.0 | 1000 | 3.0600 | 1.0 | |
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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 2.16.1 |
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- Tokenizers 0.15.0 |
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