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--- |
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base_model: linker_v5/stage1 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- jarod0411/linker_v3 |
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metrics: |
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- accuracy |
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model-index: |
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- name: stage2_v5 |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: jarod0411/linker_v3 |
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type: jarod0411/linker_v3 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.916456858900755 |
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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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# stage2_v5 |
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This model is a fine-tuned version of [linker_v5/stage1](https://huggingface.co./linker_v5/stage1) on the jarod0411/linker_v3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2448 |
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- Accuracy: 0.9165 |
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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: 1 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 192 |
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- total_eval_batch_size: 192 |
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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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- num_epochs: 10.0 |
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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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| 0.3173 | 1.0 | 11304 | 0.2837 | 0.9060 | |
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| 0.284 | 2.0 | 22608 | 0.2613 | 0.9124 | |
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| 0.2719 | 3.0 | 33912 | 0.2546 | 0.9140 | |
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| 0.2654 | 4.0 | 45216 | 0.2511 | 0.9148 | |
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| 0.2613 | 5.0 | 56520 | 0.2489 | 0.9154 | |
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| 0.2586 | 6.0 | 67824 | 0.2474 | 0.9158 | |
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| 0.2569 | 7.0 | 79128 | 0.2463 | 0.9161 | |
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| 0.2553 | 8.0 | 90432 | 0.2455 | 0.9163 | |
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| 0.2545 | 9.0 | 101736 | 0.2450 | 0.9164 | |
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| 0.2539 | 10.0 | 113040 | 0.2448 | 0.9165 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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