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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_F04 |
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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_F04 |
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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: 1.4132 |
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- Wer: 0.2275 |
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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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| 3.4699 | 0.85 | 1000 | 3.2861 | 1.0 | |
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| 2.1971 | 1.69 | 2000 | 2.0008 | 0.8514 | |
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| 0.9545 | 2.54 | 3000 | 1.4512 | 0.6358 | |
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| 0.6665 | 3.39 | 4000 | 1.4047 | 0.5008 | |
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| 0.5094 | 4.24 | 5000 | 1.3973 | 0.4457 | |
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| 0.4719 | 5.08 | 6000 | 1.4290 | 0.4066 | |
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| 0.4183 | 5.93 | 7000 | 1.4807 | 0.3761 | |
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| 0.3525 | 6.78 | 8000 | 1.5710 | 0.3667 | |
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| 0.3112 | 7.63 | 9000 | 1.4555 | 0.3268 | |
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| 0.2876 | 8.47 | 10000 | 1.4537 | 0.2988 | |
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| 0.2321 | 9.32 | 11000 | 1.6268 | 0.3200 | |
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| 0.2456 | 10.17 | 12000 | 1.3804 | 0.2852 | |
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| 0.2376 | 11.02 | 13000 | 1.6112 | 0.3141 | |
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| 0.2169 | 11.86 | 14000 | 1.4480 | 0.2988 | |
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| 0.2106 | 12.71 | 15000 | 1.6790 | 0.2929 | |
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| 0.2055 | 13.56 | 16000 | 1.5383 | 0.2963 | |
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| 0.1601 | 14.41 | 17000 | 1.4142 | 0.2555 | |
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| 0.1631 | 15.25 | 18000 | 1.5318 | 0.2470 | |
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| 0.1481 | 16.1 | 19000 | 1.6078 | 0.2453 | |
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| 0.1374 | 16.95 | 20000 | 1.3588 | 0.2360 | |
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| 0.1349 | 17.8 | 21000 | 1.3788 | 0.2309 | |
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| 0.1284 | 18.64 | 22000 | 1.4818 | 0.2326 | |
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| 0.1328 | 19.49 | 23000 | 1.4132 | 0.2275 | |
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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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