2719ad1d5d
Model: ali-elganzory/sft_ot30k_1.7b-MixtureVitae-300BT-v1-decontaminated-16k-SFT-Tulu3-decontaminated_v0 Source: Original Platform
62 lines
1.7 KiB
Markdown
62 lines
1.7 KiB
Markdown
---
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library_name: transformers
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license: other
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base_model: ali-elganzory/1.7b-MixtureVitae-300BT-v1-16k-SFT-Tulu3
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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: sft_1-7b-Mixt-300B-v1-16k-SFT-Tulu_open-thou_Open-1-2M_3000_samp_temp_open-sci_save-stra_step_1-
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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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# sft_1-7b-Mixt-300B-v1-16k-SFT-Tulu_open-thou_Open-1-2M_3000_samp_temp_open-sci_save-stra_step_1-
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This model is a fine-tuned version of [ali-elganzory/1.7b-MixtureVitae-300BT-v1-16k-SFT-Tulu3](https://huggingface.co/ali-elganzory/1.7b-MixtureVitae-300BT-v1-16k-SFT-Tulu3) on the /e/scratch/jureap59/ot/datasets/open-thoughts_OpenThoughts3-1.2M_30000_samples dataset.
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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: 4e-05
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- train_batch_size: 1
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 32
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 256
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 5.0
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### Training results
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### Framework versions
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- Transformers 4.55.0
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- Pytorch 2.9.0+cu129
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- Datasets 4.5.0
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- Tokenizers 0.21.1
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