934e39a31c
Model: huseyinatahaninan/appworld_distillation_sft_v2-SFT-Qwen3-4B-Instruct-2507 Source: Original Platform
95 lines
3.1 KiB
Markdown
95 lines
3.1 KiB
Markdown
---
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library_name: transformers
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license: apache-2.0
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base_model: Qwen/Qwen3-4B-Instruct-2507
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tags:
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- llama-factory
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- full
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- generated_from_trainer
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model-index:
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- name: appworld_distillation_sft_v2-SFT-Qwen3-4B-Instruct-2507
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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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# appworld_distillation_sft_v2-SFT-Qwen3-4B-Instruct-2507
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This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the appworld_distillation_sft_v2 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7486
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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-06
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- train_batch_size: 4
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 32
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- total_eval_batch_size: 8
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 30.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.7313 | 1.0 | 2 | 1.7900 |
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| 1.6378 | 2.0 | 4 | 1.5365 |
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| 1.1356 | 3.0 | 6 | 1.1186 |
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| 0.9041 | 4.0 | 8 | 0.9372 |
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| 0.8762 | 5.0 | 10 | 0.8529 |
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| 0.7807 | 6.0 | 12 | 0.8198 |
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| 0.7323 | 7.0 | 14 | 0.7646 |
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| 0.6814 | 8.0 | 16 | 0.7229 |
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| 0.6211 | 9.0 | 18 | 0.6847 |
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| 0.5738 | 10.0 | 20 | 0.6639 |
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| 0.5171 | 11.0 | 22 | 0.6499 |
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| 0.4868 | 12.0 | 24 | 0.6385 |
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| 0.4371 | 13.0 | 26 | 0.6327 |
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| 0.407 | 14.0 | 28 | 0.6306 |
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| 0.3924 | 15.0 | 30 | 0.6330 |
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| 0.3505 | 16.0 | 32 | 0.6393 |
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| 0.3339 | 17.0 | 34 | 0.6493 |
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| 0.3086 | 18.0 | 36 | 0.6623 |
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| 0.2803 | 19.0 | 38 | 0.6748 |
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| 0.2687 | 20.0 | 40 | 0.6873 |
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| 0.25 | 21.0 | 42 | 0.6983 |
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| 0.2306 | 22.0 | 44 | 0.7100 |
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| 0.2168 | 23.0 | 46 | 0.7205 |
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| 0.2125 | 24.0 | 48 | 0.7301 |
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| 0.2031 | 25.0 | 50 | 0.7378 |
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| 0.1975 | 26.0 | 52 | 0.7433 |
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| 0.2001 | 27.0 | 54 | 0.7474 |
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| 0.1953 | 28.0 | 56 | 0.7487 |
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| 0.1895 | 29.0 | 58 | 0.7487 |
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| 0.1976 | 30.0 | 60 | 0.7486 |
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### Framework versions
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- Transformers 4.52.4
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- Pytorch 2.8.0+cu128
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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