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--- |
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base_model: Qwen/Qwen-14B |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: nampdn-ai_tiny-textbooks |
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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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# nampdn-ai_tiny-textbooks |
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This model is a fine-tuned version of [Qwen/Qwen-14B](https://huggingface.co/Qwen/Qwen-14B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3572 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 0.01 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.4651 | 0.02 | 200 | 2.3996 | |
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| 2.4335 | 0.04 | 400 | 2.3799 | |
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| 2.3848 | 0.06 | 600 | 2.3746 | |
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| 2.4037 | 0.08 | 800 | 2.3714 | |
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| 2.3985 | 0.1 | 1000 | 2.3693 | |
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| 2.4072 | 0.12 | 1200 | 2.3673 | |
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| 2.4028 | 0.14 | 1400 | 2.3665 | |
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| 2.3748 | 0.16 | 1600 | 2.3643 | |
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| 2.4119 | 0.18 | 1800 | 2.3635 | |
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| 2.4002 | 0.2 | 2000 | 2.3640 | |
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| 2.3865 | 0.22 | 2200 | 2.3635 | |
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| 2.4 | 0.24 | 2400 | 2.3628 | |
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| 2.4096 | 0.26 | 2600 | 2.3625 | |
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| 2.3976 | 0.28 | 2800 | 2.3614 | |
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| 2.3767 | 0.3 | 3000 | 2.3618 | |
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| 2.4151 | 0.32 | 3200 | 2.3616 | |
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| 2.3835 | 0.34 | 3400 | 2.3605 | |
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| 2.3995 | 0.36 | 3600 | 2.3608 | |
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| 2.4121 | 0.38 | 3800 | 2.3602 | |
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| 2.4262 | 0.4 | 4000 | 2.3591 | |
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| 2.3604 | 0.42 | 4200 | 2.3594 | |
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| 2.3954 | 0.44 | 4400 | 2.3594 | |
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| 2.3743 | 0.46 | 4600 | 2.3587 | |
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| 2.4069 | 0.48 | 4800 | 2.3591 | |
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| 2.4103 | 0.5 | 5000 | 2.3585 | |
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| 2.4133 | 0.52 | 5200 | 2.3585 | |
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| 2.4229 | 0.54 | 5400 | 2.3578 | |
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| 2.4397 | 0.56 | 5600 | 2.3581 | |
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| 2.4237 | 0.58 | 5800 | 2.3581 | |
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| 2.4109 | 0.6 | 6000 | 2.3577 | |
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| 2.43 | 0.62 | 6200 | 2.3575 | |
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| 2.3999 | 0.64 | 6400 | 2.3572 | |
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| 2.3771 | 0.66 | 6600 | 2.3577 | |
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| 2.4119 | 0.68 | 6800 | 2.3576 | |
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| 2.3877 | 0.7 | 7000 | 2.3576 | |
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| 2.411 | 0.72 | 7200 | 2.3569 | |
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| 2.3808 | 0.74 | 7400 | 2.3570 | |
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| 2.3989 | 0.76 | 7600 | 2.3571 | |
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| 2.422 | 0.78 | 7800 | 2.3569 | |
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| 2.3768 | 0.8 | 8000 | 2.3569 | |
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| 2.3988 | 0.82 | 8200 | 2.3572 | |
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| 2.3927 | 0.84 | 8400 | 2.3572 | |
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| 2.3961 | 0.86 | 8600 | 2.3573 | |
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| 2.4021 | 0.88 | 8800 | 2.3570 | |
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| 2.3889 | 0.9 | 9000 | 2.3570 | |
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| 2.404 | 0.92 | 9200 | 2.3570 | |
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| 2.3982 | 0.94 | 9400 | 2.3572 | |
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| 2.4018 | 0.96 | 9600 | 2.3573 | |
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| 2.3717 | 0.98 | 9800 | 2.3572 | |
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| 2.4076 | 1.0 | 10000 | 2.3572 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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