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---
base_model: Qwen/Qwen-14B
tags:
- generated_from_trainer
model-index:
- name: nampdn-ai_tiny-textbooks
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# nampdn-ai_tiny-textbooks
This model is a fine-tuned version of [Qwen/Qwen-14B](https://huggingface.co/Qwen/Qwen-14B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3572
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.01
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.4651 | 0.02 | 200 | 2.3996 |
| 2.4335 | 0.04 | 400 | 2.3799 |
| 2.3848 | 0.06 | 600 | 2.3746 |
| 2.4037 | 0.08 | 800 | 2.3714 |
| 2.3985 | 0.1 | 1000 | 2.3693 |
| 2.4072 | 0.12 | 1200 | 2.3673 |
| 2.4028 | 0.14 | 1400 | 2.3665 |
| 2.3748 | 0.16 | 1600 | 2.3643 |
| 2.4119 | 0.18 | 1800 | 2.3635 |
| 2.4002 | 0.2 | 2000 | 2.3640 |
| 2.3865 | 0.22 | 2200 | 2.3635 |
| 2.4 | 0.24 | 2400 | 2.3628 |
| 2.4096 | 0.26 | 2600 | 2.3625 |
| 2.3976 | 0.28 | 2800 | 2.3614 |
| 2.3767 | 0.3 | 3000 | 2.3618 |
| 2.4151 | 0.32 | 3200 | 2.3616 |
| 2.3835 | 0.34 | 3400 | 2.3605 |
| 2.3995 | 0.36 | 3600 | 2.3608 |
| 2.4121 | 0.38 | 3800 | 2.3602 |
| 2.4262 | 0.4 | 4000 | 2.3591 |
| 2.3604 | 0.42 | 4200 | 2.3594 |
| 2.3954 | 0.44 | 4400 | 2.3594 |
| 2.3743 | 0.46 | 4600 | 2.3587 |
| 2.4069 | 0.48 | 4800 | 2.3591 |
| 2.4103 | 0.5 | 5000 | 2.3585 |
| 2.4133 | 0.52 | 5200 | 2.3585 |
| 2.4229 | 0.54 | 5400 | 2.3578 |
| 2.4397 | 0.56 | 5600 | 2.3581 |
| 2.4237 | 0.58 | 5800 | 2.3581 |
| 2.4109 | 0.6 | 6000 | 2.3577 |
| 2.43 | 0.62 | 6200 | 2.3575 |
| 2.3999 | 0.64 | 6400 | 2.3572 |
| 2.3771 | 0.66 | 6600 | 2.3577 |
| 2.4119 | 0.68 | 6800 | 2.3576 |
| 2.3877 | 0.7 | 7000 | 2.3576 |
| 2.411 | 0.72 | 7200 | 2.3569 |
| 2.3808 | 0.74 | 7400 | 2.3570 |
| 2.3989 | 0.76 | 7600 | 2.3571 |
| 2.422 | 0.78 | 7800 | 2.3569 |
| 2.3768 | 0.8 | 8000 | 2.3569 |
| 2.3988 | 0.82 | 8200 | 2.3572 |
| 2.3927 | 0.84 | 8400 | 2.3572 |
| 2.3961 | 0.86 | 8600 | 2.3573 |
| 2.4021 | 0.88 | 8800 | 2.3570 |
| 2.3889 | 0.9 | 9000 | 2.3570 |
| 2.404 | 0.92 | 9200 | 2.3570 |
| 2.3982 | 0.94 | 9400 | 2.3572 |
| 2.4018 | 0.96 | 9600 | 2.3573 |
| 2.3717 | 0.98 | 9800 | 2.3572 |
| 2.4076 | 1.0 | 10000 | 2.3572 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.5
- Tokenizers 0.14.1
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