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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: seq2seq_huggingface_mix_results |
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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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# seq2seq_huggingface_mix_results |
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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: 7.9457 |
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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: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 48 |
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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_steps: 500 |
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- num_epochs: 1 |
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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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| 10.7021 | 0.0480 | 10 | 10.6458 | |
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| 10.5611 | 0.0959 | 20 | 10.4143 | |
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| 10.2935 | 0.1439 | 30 | 10.0786 | |
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| 9.9673 | 0.1918 | 40 | 9.7462 | |
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| 9.6468 | 0.2398 | 50 | 9.4724 | |
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| 9.4303 | 0.2878 | 60 | 9.2583 | |
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| 9.2452 | 0.3357 | 70 | 9.1136 | |
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| 9.1357 | 0.3837 | 80 | 9.0100 | |
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| 9.0307 | 0.4317 | 90 | 8.9296 | |
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| 8.9363 | 0.4796 | 100 | 8.8591 | |
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| 8.8781 | 0.5276 | 110 | 8.7821 | |
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| 8.7907 | 0.5755 | 120 | 8.7088 | |
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| 8.7214 | 0.6235 | 130 | 8.6329 | |
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| 8.6375 | 0.6715 | 140 | 8.5511 | |
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| 8.5439 | 0.7194 | 150 | 8.4701 | |
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| 8.4715 | 0.7674 | 160 | 8.3835 | |
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| 8.389 | 0.8153 | 170 | 8.2962 | |
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| 8.2787 | 0.8633 | 180 | 8.2072 | |
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| 8.1826 | 0.9113 | 190 | 8.1146 | |
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| 8.0848 | 0.9592 | 200 | 8.0225 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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