Model: ali-elganzory/sft_ot30k_1.7b-MixtureVitae-300BT-v1-decontaminated-16k-SFT-Tulu3-decontaminated_v0 Source: Original Platform
library_name, license, base_model, tags, model-index
| library_name | license | base_model | tags | model-index | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | other | ali-elganzory/1.7b-MixtureVitae-300BT-v1-16k-SFT-Tulu3 |
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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-
This model is a fine-tuned version of 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.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.55.0
- Pytorch 2.9.0+cu129
- Datasets 4.5.0
- Tokenizers 0.21.1
Description
Model synced from source: ali-elganzory/sft_ot30k_1.7b-MixtureVitae-300BT-v1-decontaminated-16k-SFT-Tulu3-decontaminated_v0
Languages
Python
98.6%
Jinja
1.4%