75 lines
2.2 KiB
Markdown
75 lines
2.2 KiB
Markdown
---
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library_name: transformers
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base_model: davron04/gemma-3-270m-uzen-base
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tags:
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- generated_from_trainer
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model-index:
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- name: gemma-3-270m-uzen-base
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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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# gemma-3-270m-uzen-base
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This model is a fine-tuned version of [davron04/gemma-3-270m-uzen-base](https://huggingface.co/davron04/gemma-3-270m-uzen-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1987
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- Perplexity: 9.0416
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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: 2
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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: 2
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- gradient_accumulation_steps: 64
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- total_train_batch_size: 256
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- total_eval_batch_size: 8
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- optimizer: Use OptimizerNames.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: inverse_sqrt
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- lr_scheduler_warmup_steps: 0.01
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Perplexity |
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|:-------------:|:------:|:----:|:---------------:|:----------:|
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| No log | 0 | 0 | 3.3726 | 29.0075 |
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| 152.2381 | 0.1002 | 428 | 2.4411 | 11.5116 |
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| 145.3987 | 0.2003 | 856 | 2.3491 | 10.5032 |
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| 143.7446 | 0.3005 | 1284 | 2.3286 | 10.2931 |
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| 140.7659 | 0.4006 | 1712 | 2.2912 | 9.9159 |
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| 139.1574 | 0.5008 | 2140 | 2.2643 | 9.6535 |
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| 137.4137 | 0.6009 | 2568 | 2.2431 | 9.4512 |
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| 136.3983 | 0.7011 | 2996 | 2.2254 | 9.2859 |
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| 135.6059 | 0.8012 | 3424 | 2.2111 | 9.1541 |
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| 134.8424 | 0.9014 | 3852 | 2.1987 | 9.0416 |
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### Framework versions
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- Transformers 5.0.0
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- Pytorch 2.10.0+cu128
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- Datasets 4.8.5
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- Tokenizers 0.22.2
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