--- library_name: transformers license: apache-2.0 base_model: BEE-spoke-data/tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024 tags: - generated_from_trainer model-index: - name: tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024-infinity-instruct-7m-T2T_en-1024-v2 results: [] --- # tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024-infinity-instruct-7m-T2T_en-1024-v2 This model is a fine-tuned version of [BEE-spoke-data/tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024](https://huggingface.co/BEE-spoke-data/tFINE-900m-e16-d32-flan-infinity-instruct-7m-T2T_en-1024) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1160 - Num Input Tokens Seen: 785755388 ## 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: 5e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 6969 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 16 - total_train_batch_size: 128 - total_eval_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 1.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Input Tokens Seen | |:-------------:|:------:|:-----:|:---------------:|:-----------------:| | 1.234 | 0.0969 | 2000 | 1.2439 | 78067836 | | 1.2248 | 0.1938 | 4000 | 1.2256 | 156868756 | | 1.2024 | 0.2907 | 6000 | 1.2009 | 235148092 | | 1.2074 | 0.3876 | 8000 | 1.1777 | 313452856 | | 1.1617 | 0.4845 | 10000 | 1.1597 | 392316428 | | 1.1755 | 0.5815 | 12000 | 1.1437 | 471101508 | | 1.1473 | 0.6784 | 14000 | 1.1321 | 549831184 | | 1.1743 | 0.7753 | 16000 | 1.1244 | 628937800 | | 1.137 | 0.8722 | 18000 | 1.1179 | 707117360 | | 1.0713 | 0.9691 | 20000 | 1.1160 | 785755388 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1