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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: my_run |
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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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# my_run |
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.4043 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 128 |
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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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- training_steps: 1000000 |
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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 | |
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|:-------------:|:-----:|:-------:|:---------------:| |
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| 7.1589 | 1.81 | 50000 | 6.8011 | |
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| 6.7421 | 3.62 | 100000 | 6.6767 | |
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| 6.6503 | 5.42 | 150000 | 6.6086 | |
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| 6.5951 | 7.23 | 200000 | 6.5605 | |
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| 6.5566 | 9.04 | 250000 | 6.5271 | |
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| 6.5292 | 10.85 | 300000 | 6.5037 | |
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| 6.5069 | 12.65 | 350000 | 6.4839 | |
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| 6.49 | 14.46 | 400000 | 6.4667 | |
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| 6.4759 | 16.27 | 450000 | 6.4552 | |
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| 6.4648 | 18.08 | 500000 | 6.4442 | |
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| 6.4551 | 19.88 | 550000 | 6.4365 | |
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| 6.4475 | 21.69 | 600000 | 6.4278 | |
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| 6.4412 | 23.5 | 650000 | 6.4222 | |
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| 6.4358 | 25.31 | 700000 | 6.4185 | |
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| 6.4313 | 27.11 | 750000 | 6.4134 | |
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| 6.4275 | 28.92 | 800000 | 6.4110 | |
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| 6.425 | 30.73 | 850000 | 6.4079 | |
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| 6.4229 | 32.54 | 900000 | 6.4063 | |
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| 6.4218 | 34.35 | 950000 | 6.4047 | |
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| 6.4204 | 36.15 | 1000000 | 6.4043 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.3.0a0+ebedce2 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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