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README.md
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---
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base_model: final_models/focus_bur_phi_after_focus_reinit
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tags:
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- generated_from_trainer
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datasets:
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- mc4
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model-index:
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- name: focus_bur_phi_focus_trained
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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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# focus_bur_phi_focus_trained
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This model is a fine-tuned version of [final_models/focus_bur_phi_after_focus_reinit](https://huggingface.co/final_models/focus_bur_phi_after_focus_reinit) on the mc4 my dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.8202
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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: 0.0003
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 2000
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- num_epochs: 6.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:------:|:---------------:|
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| 1.5881 | 1.0 | 24415 | 2.1758 |
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| 1.8 | 2.0 | 48830 | 2.0561 |
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| 2.4986 | 3.0 | 73245 | 1.9480 |
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| 0.9893 | 4.0 | 97660 | 1.8157 |
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| 1.0487 | 5.0 | 122075 | 1.7515 |
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| 0.8305 | 6.0 | 146490 | 1.8202 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.19.1
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