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mini-chennus-2

Text Generation
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Safetensors
gpt_neox
Generated from Trainer
text-generation-inference
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: EleutherAI/pythia-14m-deduped
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: chennus-mini-2
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+ results: []
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+ ---
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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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+
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+ # chennus-mini-2
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+
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+ This model is a fine-tuned version of [EleutherAI/pythia-14m-deduped](https://huggingface.co/EleutherAI/pythia-14m-deduped) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: nan
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+ - Accuracy: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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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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+ - num_epochs: 6
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.0 | 0.1616 | 200 | nan | 0.0 |
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+ | 0.0 | 0.3231 | 400 | nan | 0.0 |
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+ | 0.0 | 0.4847 | 600 | nan | 0.0 |
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+ | 0.0 | 0.6462 | 800 | nan | 0.0 |
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+ | 0.0 | 0.8078 | 1000 | nan | 0.0 |
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+ | 0.0 | 0.9693 | 1200 | nan | 0.0 |
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+ | 0.0 | 1.1309 | 1400 | nan | 0.0 |
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+ | 0.0 | 1.2924 | 1600 | nan | 0.0 |
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+ | 0.0 | 1.4540 | 1800 | nan | 0.0 |
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+ | 0.0 | 1.6155 | 2000 | nan | 0.0 |
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+ | 0.0 | 1.7771 | 2200 | nan | 0.0 |
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+ | 0.0 | 1.9386 | 2400 | nan | 0.0 |
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+ | 0.0 | 2.1002 | 2600 | nan | 0.0 |
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+ | 0.0 | 2.2617 | 2800 | nan | 0.0 |
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+ | 0.0 | 2.4233 | 3000 | nan | 0.0 |
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+ | 0.0 | 2.5848 | 3200 | nan | 0.0 |
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+ | 0.0 | 2.7464 | 3400 | nan | 0.0 |
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+ | 0.0 | 2.9079 | 3600 | nan | 0.0 |
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+ | 0.0 | 3.0695 | 3800 | nan | 0.0 |
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+ | 0.0 | 3.2310 | 4000 | nan | 0.0 |
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+ | 0.0 | 3.3926 | 4200 | nan | 0.0 |
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+ | 0.0 | 3.5541 | 4400 | nan | 0.0 |
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+ | 0.0 | 3.7157 | 4600 | nan | 0.0 |
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+ | 0.0 | 3.8772 | 4800 | nan | 0.0 |
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+ | 0.0 | 4.0388 | 5000 | nan | 0.0 |
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+ | 0.0 | 4.2003 | 5200 | nan | 0.0 |
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+ | 0.0 | 4.3619 | 5400 | nan | 0.0 |
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+ | 0.0 | 4.5234 | 5600 | nan | 0.0 |
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+ | 0.0 | 4.6850 | 5800 | nan | 0.0 |
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+ | 0.0 | 4.8465 | 6000 | nan | 0.0 |
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+ | 0.0 | 5.0081 | 6200 | nan | 0.0 |
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+ | 0.0 | 5.1696 | 6400 | nan | 0.0 |
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+ | 0.0 | 5.3312 | 6600 | nan | 0.0 |
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+ | 0.0 | 5.4927 | 6800 | nan | 0.0 |
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+ | 0.0 | 5.6543 | 7000 | nan | 0.0 |
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+ | 0.0 | 5.8158 | 7200 | nan | 0.0 |
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+ | 0.0 | 5.9774 | 7400 | nan | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 5.0.0
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+ - Pytorch 2.10.0+cu128
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.2
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