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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Qwen/Qwen2.5-0.5B |
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tags: |
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- generated_from_trainer |
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- qwen |
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- GGUF |
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- worldmodel |
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- worldbuilding |
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model-index: |
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- name: capybara_finetuned_results3 |
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results: [] |
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datasets: |
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- archit11/worldbuilding |
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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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# capybara_finetuned_results3 |
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This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.6542 |
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## video demo : (its pretty bad) |
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<video controls autoplay muted src="https://0x0.st/XgZs.mp4"></video> |
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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: 0.0002 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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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: 5 |
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- training_steps: 800 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 15.5311 | 0.0230 | 50 | 14.5422 | |
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| 8.7477 | 0.0460 | 100 | 9.2952 | |
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| 7.3554 | 0.0690 | 150 | 7.1992 | |
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| 6.828 | 0.0920 | 200 | 6.7258 | |
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| 6.4694 | 0.1150 | 250 | 6.3597 | |
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| 6.3401 | 0.1381 | 300 | 6.1703 | |
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| 6.1256 | 0.1611 | 350 | 6.0395 | |
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| 6.0372 | 0.1841 | 400 | 5.9271 | |
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| 6.0221 | 0.2071 | 450 | 5.8464 | |
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| 5.8783 | 0.2301 | 500 | 5.7810 | |
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| 5.8339 | 0.2531 | 550 | 5.7335 | |
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| 5.8546 | 0.2761 | 600 | 5.6904 | |
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| 5.9169 | 0.2991 | 650 | 5.6690 | |
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| 5.7959 | 0.3221 | 700 | 5.6565 | |
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| 5.7271 | 0.3451 | 750 | 5.6543 | |
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| 5.8734 | 0.3682 | 800 | 5.6542 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
