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--- |
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license: apache-2.0 |
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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: torgo_xlsr_finetune_M05 |
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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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# torgo_xlsr_finetune_M05 |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2781 |
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- Wer: 0.2436 |
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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: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 20 |
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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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| 3.5164 | 0.84 | 1000 | 3.3225 | 1.0 | |
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| 1.535 | 1.68 | 2000 | 1.5429 | 0.7317 | |
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| 0.8257 | 2.53 | 3000 | 1.3691 | 0.5730 | |
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| 0.6012 | 3.37 | 4000 | 1.2522 | 0.4660 | |
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| 0.491 | 4.21 | 5000 | 1.1413 | 0.4295 | |
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| 0.4401 | 5.05 | 6000 | 1.4117 | 0.3744 | |
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| 0.3768 | 5.89 | 7000 | 1.3632 | 0.3531 | |
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| 0.3746 | 6.73 | 8000 | 1.4208 | 0.3557 | |
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| 0.3127 | 7.58 | 9000 | 1.3584 | 0.3336 | |
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| 0.2595 | 8.42 | 10000 | 0.9971 | 0.2878 | |
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| 0.2458 | 9.26 | 11000 | 1.2794 | 0.3166 | |
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| 0.2638 | 10.1 | 12000 | 1.1851 | 0.2861 | |
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| 0.2384 | 10.94 | 13000 | 1.2144 | 0.2810 | |
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| 0.215 | 11.78 | 14000 | 1.1125 | 0.2623 | |
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| 0.2095 | 12.63 | 15000 | 1.5495 | 0.3081 | |
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| 0.1939 | 13.47 | 16000 | 1.4090 | 0.2818 | |
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| 0.1757 | 14.31 | 17000 | 1.3261 | 0.2564 | |
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| 0.1629 | 15.15 | 18000 | 1.3435 | 0.2453 | |
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| 0.152 | 15.99 | 19000 | 1.3273 | 0.2479 | |
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| 0.1516 | 16.84 | 20000 | 1.2215 | 0.2292 | |
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| 0.155 | 17.68 | 21000 | 1.3536 | 0.2453 | |
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| 0.135 | 18.52 | 22000 | 1.3292 | 0.2470 | |
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| 0.1206 | 19.36 | 23000 | 1.2781 | 0.2436 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.13.3 |
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