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--- |
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license: apache-2.0 |
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base_model: facebook/hubert-base-ls960 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: hubert-base-ls960-finetuned-ic-slurp |
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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-base-ls960-finetuned-ic-slurp |
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9150 |
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- Accuracy: 0.7349 |
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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: 5e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 96 |
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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_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 4.0503 | 1.0 | 527 | 3.9739 | 0.0814 | |
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| 3.8351 | 2.0 | 1055 | 3.7950 | 0.0837 | |
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| 3.7053 | 3.0 | 1582 | 3.6592 | 0.1081 | |
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| 3.4539 | 4.0 | 2110 | 3.3374 | 0.1772 | |
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| 2.657 | 5.0 | 2637 | 2.5832 | 0.3443 | |
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| 2.1356 | 6.0 | 3165 | 2.0006 | 0.4873 | |
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| 1.7409 | 7.0 | 3692 | 1.7459 | 0.5627 | |
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| 1.4391 | 8.0 | 4220 | 1.6168 | 0.6104 | |
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| 1.1336 | 9.0 | 4747 | 1.5041 | 0.6489 | |
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| 1.0151 | 10.0 | 5275 | 1.4378 | 0.6786 | |
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| 0.8624 | 11.0 | 5802 | 1.4653 | 0.6880 | |
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| 0.6583 | 12.0 | 6330 | 1.4319 | 0.6998 | |
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| 0.7089 | 13.0 | 6857 | 1.4993 | 0.7095 | |
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| 0.6454 | 14.0 | 7385 | 1.5267 | 0.7036 | |
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| 0.5424 | 15.0 | 7912 | 1.5672 | 0.7152 | |
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| 0.425 | 16.0 | 8440 | 1.6051 | 0.7159 | |
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| 0.4016 | 17.0 | 8967 | 1.6342 | 0.7173 | |
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| 0.3563 | 18.0 | 9495 | 1.7061 | 0.7110 | |
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| 0.367 | 19.0 | 10022 | 1.6884 | 0.7177 | |
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| 0.3511 | 20.0 | 10550 | 1.7300 | 0.7154 | |
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| 0.3573 | 21.0 | 11077 | 1.7361 | 0.7230 | |
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| 0.2533 | 22.0 | 11605 | 1.7119 | 0.7279 | |
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| 0.2029 | 23.0 | 12132 | 1.7801 | 0.7279 | |
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| 0.3279 | 24.0 | 12660 | 1.8096 | 0.7324 | |
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| 0.2164 | 25.0 | 13187 | 1.8916 | 0.7237 | |
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| 0.2092 | 26.0 | 13715 | 1.8348 | 0.7274 | |
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| 0.1757 | 27.0 | 14242 | 1.8824 | 0.7286 | |
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| 0.2584 | 28.0 | 14770 | 1.9150 | 0.7349 | |
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| 0.1605 | 29.0 | 15297 | 1.9417 | 0.7305 | |
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| 0.1815 | 30.0 | 15825 | 1.8939 | 0.7309 | |
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| 0.1749 | 31.0 | 16352 | 1.9729 | 0.7327 | |
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| 0.1628 | 32.0 | 16880 | 1.9796 | 0.7275 | |
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| 0.1369 | 33.0 | 17407 | 2.0156 | 0.7322 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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