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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- anli |
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base_model: EleutherAI/gpt-j-6b |
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model-index: |
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- name: sft-trl-claim-128 |
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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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# sft-trl-claim-128 |
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This model is a fine-tuned version of [EleutherAI/gpt-j-6b](https://huggingface.co/EleutherAI/gpt-j-6b) on the anli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3201 |
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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_steps: 100 |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 1.4364 | 0.08 | 1000 | 1.8760 | |
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| 0.9805 | 0.16 | 2000 | 1.2595 | |
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| 0.6629 | 0.24 | 3000 | 1.2970 | |
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| 0.4647 | 0.32 | 4000 | 0.9789 | |
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| 0.4579 | 0.4 | 5000 | 0.8591 | |
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| 0.383 | 0.48 | 6000 | 0.8866 | |
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| 0.4915 | 0.56 | 7000 | 0.4281 | |
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| 0.4139 | 0.64 | 8000 | 0.3946 | |
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| 0.2563 | 0.72 | 9000 | 0.3653 | |
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| 0.3179 | 0.8 | 10000 | 0.3528 | |
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| 0.4199 | 0.88 | 11000 | 0.3602 | |
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| 0.3877 | 0.96 | 12000 | 0.3457 | |
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| 0.2332 | 1.04 | 13000 | 0.3882 | |
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| 0.3817 | 1.11 | 14000 | 0.3604 | |
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| 0.2734 | 1.19 | 15000 | 0.3613 | |
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| 0.213 | 1.27 | 16000 | 0.3722 | |
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| 0.3154 | 1.35 | 17000 | 0.3378 | |
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| 0.2258 | 1.43 | 18000 | 0.3117 | |
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| 0.3198 | 1.51 | 19000 | 0.3213 | |
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| 0.2959 | 1.59 | 20000 | 0.3050 | |
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| 0.2588 | 1.67 | 21000 | 0.3190 | |
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| 0.2279 | 1.75 | 22000 | 0.3065 | |
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| 0.2988 | 1.83 | 23000 | 0.3077 | |
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| 0.3701 | 1.91 | 24000 | 0.3092 | |
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| 0.281 | 1.99 | 25000 | 0.3038 | |
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| 0.1743 | 2.07 | 26000 | 0.3542 | |
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| 0.1374 | 2.15 | 27000 | 0.3550 | |
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| 0.1282 | 2.23 | 28000 | 0.3386 | |
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| 0.1757 | 2.31 | 29000 | 0.3489 | |
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| 0.1371 | 2.39 | 30000 | 0.3316 | |
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| 0.1689 | 2.47 | 31000 | 0.3291 | |
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| 0.1882 | 2.55 | 32000 | 0.3292 | |
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| 0.1685 | 2.63 | 33000 | 0.3196 | |
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| 0.1775 | 2.71 | 34000 | 0.3320 | |
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| 0.1963 | 2.79 | 35000 | 0.3278 | |
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| 0.1733 | 2.87 | 36000 | 0.3221 | |
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| 0.1503 | 2.95 | 37000 | 0.3201 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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