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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-wt_init-frz |
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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-wt_init-frz |
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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: 3.0889 |
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- Accuracy: 0.4598 |
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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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| 3.6605 | 1.0 | 527 | 3.6385 | 0.1020 | |
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| 3.6135 | 2.0 | 1055 | 3.5710 | 0.1200 | |
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| 3.4222 | 3.0 | 1582 | 3.3394 | 0.1738 | |
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| 3.1948 | 4.0 | 2110 | 3.2132 | 0.2052 | |
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| 2.8791 | 5.0 | 2637 | 2.9508 | 0.2581 | |
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| 2.7807 | 6.0 | 3165 | 2.7201 | 0.3109 | |
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| 2.4647 | 7.0 | 3692 | 2.6056 | 0.3393 | |
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| 2.3009 | 8.0 | 4220 | 2.4893 | 0.3816 | |
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| 2.0953 | 9.0 | 4747 | 2.4874 | 0.3902 | |
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| 1.8074 | 10.0 | 5275 | 2.4705 | 0.4035 | |
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| 1.8209 | 11.0 | 5802 | 2.4465 | 0.4177 | |
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| 1.4822 | 12.0 | 6330 | 2.5310 | 0.4228 | |
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| 1.426 | 13.0 | 6857 | 2.5097 | 0.4305 | |
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| 1.2877 | 14.0 | 7385 | 2.5365 | 0.4368 | |
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| 1.0833 | 15.0 | 7912 | 2.5874 | 0.4404 | |
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| 1.0709 | 16.0 | 8440 | 2.6478 | 0.4373 | |
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| 0.8176 | 17.0 | 8967 | 2.7096 | 0.4409 | |
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| 0.803 | 18.0 | 9495 | 2.7965 | 0.4491 | |
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| 0.6678 | 19.0 | 10022 | 2.9335 | 0.4470 | |
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| 0.7066 | 20.0 | 10550 | 3.0013 | 0.4408 | |
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| 0.5935 | 21.0 | 11077 | 2.9613 | 0.4544 | |
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| 0.5703 | 22.0 | 11605 | 2.9915 | 0.4534 | |
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| 0.5 | 23.0 | 12132 | 3.0625 | 0.4556 | |
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| 0.55 | 24.0 | 12660 | 3.0889 | 0.4598 | |
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| 0.3977 | 25.0 | 13187 | 3.1962 | 0.4551 | |
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| 0.4578 | 26.0 | 13715 | 3.2863 | 0.4574 | |
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| 0.3343 | 27.0 | 14242 | 3.3401 | 0.4531 | |
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| 0.4414 | 28.0 | 14770 | 3.3229 | 0.4557 | |
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| 0.2551 | 29.0 | 15297 | 3.4294 | 0.4567 | |
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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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