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--- |
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license: other |
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base_model: KnutJaegersberg/Qwen-1_8B-Llamafied |
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tags: |
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- alignment-handbook |
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- trl |
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- sft |
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- generated_from_trainer |
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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- HuggingFaceH4/ultrachat_200k |
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model-index: |
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- name: qwen_1_8B_llamafied |
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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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# qwen_1_8B_llamafied |
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This model is a fine-tuned version of [KnutJaegersberg/Qwen-1_8B-Llamafied](https://huggingface.co/KnutJaegersberg/Qwen-1_8B-Llamafied) on the HuggingFaceH4/ultrachat_200k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2486 |
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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: 2e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 96 |
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- total_eval_batch_size: 16 |
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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: 120 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.3881 | 0.1 | 100 | 1.3937 | |
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| 1.3499 | 0.2 | 200 | 1.3372 | |
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| 1.3138 | 0.3 | 300 | 1.3168 | |
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| 1.3152 | 0.4 | 400 | 1.3045 | |
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| 1.2897 | 0.5 | 500 | 1.2954 | |
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| 1.28 | 0.6 | 600 | 1.2882 | |
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| 1.2669 | 0.7 | 700 | 1.2820 | |
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| 1.2591 | 0.8 | 800 | 1.2768 | |
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| 1.2447 | 0.9 | 900 | 1.2721 | |
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| 1.2867 | 1.0 | 1000 | 1.2680 | |
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| 1.1918 | 1.1 | 1100 | 1.2684 | |
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| 1.2002 | 1.2 | 1200 | 1.2660 | |
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| 1.1943 | 1.3 | 1300 | 1.2633 | |
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| 1.199 | 1.4 | 1400 | 1.2607 | |
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| 1.1887 | 1.5 | 1500 | 1.2581 | |
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| 1.1987 | 1.6 | 1600 | 1.2556 | |
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| 1.1954 | 1.7 | 1700 | 1.2534 | |
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| 1.1869 | 1.8 | 1800 | 1.2511 | |
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| 1.1744 | 1.9 | 1900 | 1.2492 | |
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| 1.1718 | 2.0 | 2000 | 1.2486 | |
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| 1.1456 | 2.1 | 2100 | 1.2532 | |
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| 1.1204 | 2.2 | 2200 | 1.2529 | |
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| 1.1347 | 2.3 | 2300 | 1.2519 | |
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| 1.1312 | 2.4 | 2400 | 1.2513 | |
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| 1.1229 | 2.5 | 2500 | 1.2508 | |
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| 1.1287 | 2.6 | 2600 | 1.2500 | |
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| 1.1252 | 2.7 | 2700 | 1.2500 | |
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| 1.139 | 2.8 | 2800 | 1.2498 | |
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| 1.1282 | 2.9 | 2900 | 1.2497 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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