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--- |
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library_name: transformers |
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base_model: RefalMachine/ruadapt_qwen2.5_3B_ext_u48_mean_init |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: ruadapt_qwen2.5_3B_ext_u48_full_lr3e4_bs256 |
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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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# ruadapt_qwen2.5_3B_ext_u48_full_lr3e4_bs256 |
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This model is a fine-tuned version of [RefalMachine/ruadapt_qwen2.5_3B_ext_u48_mean_init](https://huggingface.co/RefalMachine/ruadapt_qwen2.5_3B_ext_u48_mean_init) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4832 |
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- Accuracy: 0.4983 |
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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: 0.0003 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 64 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:-----:|:---------------:|:--------:| |
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| No log | 0.0001 | 1 | 5.8817 | 0.3107 | |
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| 2.6497 | 0.1765 | 2000 | 2.5180 | 0.4939 | |
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| 2.6174 | 0.3531 | 4000 | 2.4940 | 0.4966 | |
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| 2.5972 | 0.5296 | 6000 | 2.4866 | 0.4977 | |
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| 2.6022 | 0.7062 | 8000 | 2.4836 | 0.4982 | |
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| 2.5999 | 0.8827 | 10000 | 2.4831 | 0.4983 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04 |
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- Datasets 2.18.0 |
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- Tokenizers 0.20.1 |
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