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README.md
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---
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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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- f1
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model-index:
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- name: AV_MAE_DF1M_noCE_new
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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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# AV_MAE_DF1M_noCE_new
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2999
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- Accuracy: 0.9371
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- F1: 0.9367
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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: 8
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- eval_batch_size: 8
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- seed: 42
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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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- training_steps: 28240
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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 | Accuracy | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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| 0.4126 | 0.16 | 4517 | 0.4441 | 0.8969 | 0.8954 |
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| 0.3429 | 1.16 | 9033 | 0.3442 | 0.9153 | 0.9151 |
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| 0.9624 | 2.16 | 13549 | 0.3376 | 0.9225 | 0.9223 |
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| 0.408 | 3.16 | 18066 | 0.3046 | 0.9302 | 0.9300 |
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| 0.1189 | 4.16 | 22582 | 0.3120 | 0.9357 | 0.9354 |
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| 0.2586 | 5.16 | 27099 | 0.3090 | 0.9355 | 0.9350 |
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| 0.3502 | 6.04 | 28240 | 0.2999 | 0.9371 | 0.9367 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.2.1+cu118
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- Datasets 2.18.0
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- Tokenizers 0.15.1
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