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update model card README.md

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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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+ model-index:
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+ - name: sft-trl-claim-128
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+ results: []
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+ ---
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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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+
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+ # sft-trl-claim-128
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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