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--- |
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license: gemma |
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base_model: jkazdan/step_val_25_gemma-2-2b_hs2_iter1_sftsd2 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: augmented_step_val_25_gemma-2-2b_hs2_iter1_sftsd0 |
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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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# augmented_step_val_25_gemma-2-2b_hs2_iter1_sftsd0 |
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This model is a fine-tuned version of [jkazdan/step_val_25_gemma-2-2b_hs2_iter1_sftsd2](https://huggingface.co/jkazdan/step_val_25_gemma-2-2b_hs2_iter1_sftsd2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5241 |
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- Num Input Tokens Seen: 7902160 |
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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: 8e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 0 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Input Tokens Seen | |
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|:-------------:|:------:|:----:|:---------------:|:-----------------:| |
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| No log | 0 | 0 | 1.0950 | 0 | |
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| 1.4641 | 0.0363 | 5 | 1.0952 | 288056 | |
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| 1.2843 | 0.0726 | 10 | 1.1081 | 573696 | |
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| 1.179 | 0.1089 | 15 | 1.1363 | 864312 | |
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| 1.0141 | 0.1452 | 20 | 1.1791 | 1155592 | |
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| 0.9315 | 0.1815 | 25 | 1.2351 | 1442896 | |
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| 0.825 | 0.2178 | 30 | 1.3062 | 1738192 | |
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| 0.6513 | 0.2541 | 35 | 1.3937 | 2026640 | |
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| 0.5567 | 0.2904 | 40 | 1.4694 | 2311728 | |
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| 0.5304 | 0.3267 | 45 | 1.4723 | 2603472 | |
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| 0.372 | 0.3630 | 50 | 1.4773 | 2895216 | |
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| 0.3612 | 0.3993 | 55 | 1.4670 | 3177072 | |
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| 0.3167 | 0.4356 | 60 | 1.4953 | 3464608 | |
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| 0.2068 | 0.4719 | 65 | 1.5190 | 3749472 | |
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| 0.1664 | 0.5082 | 70 | 1.4786 | 4033064 | |
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| 0.2256 | 0.5445 | 75 | 1.4518 | 4326968 | |
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| 0.1704 | 0.5808 | 80 | 1.4577 | 4611416 | |
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| 0.1391 | 0.6171 | 85 | 1.5038 | 4903168 | |
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| 0.2488 | 0.6534 | 90 | 1.4373 | 5191528 | |
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| 0.1726 | 0.6897 | 95 | 1.5123 | 5474696 | |
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| 0.1696 | 0.7260 | 100 | 1.4582 | 5757304 | |
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| 0.1919 | 0.7623 | 105 | 1.4735 | 6047208 | |
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| 0.1987 | 0.7985 | 110 | 1.4654 | 6343824 | |
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| 0.256 | 0.8348 | 115 | 1.4215 | 6627376 | |
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| 0.0984 | 0.8711 | 120 | 1.5130 | 6915440 | |
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| 0.108 | 0.9074 | 125 | 1.4880 | 7206272 | |
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| 0.1414 | 0.9437 | 130 | 1.4197 | 7504304 | |
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| 0.1076 | 0.9800 | 135 | 1.5077 | 7784504 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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