Instructions to use moos124/code-reasoning-0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moos124/code-reasoning-0.5b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("moos124/code-reasoning-0.5b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2760, checkpoint
Browse files
last-checkpoint/adapter_model.safetensors
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last-checkpoint/optimizer.pt
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last-checkpoint/rng_state.pth
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last-checkpoint/scheduler.pt
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last-checkpoint/trainer_state.json
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"best_global_step": null,
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 0.
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"eval_steps": 500,
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"global_step":
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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| 2768 |
"mean_token_accuracy": 0.7488874278962612,
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| 2769 |
"num_tokens": 12776988.0,
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| 2770 |
"step": 2750
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}
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],
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| 2773 |
"logging_steps": 10,
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"attributes": {}
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}
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},
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"total_flos": 6.
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| 2791 |
"train_batch_size": 4,
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| 2792 |
"trial_name": null,
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| 2793 |
"trial_params": null
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"best_global_step": null,
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 0.5888,
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"eval_steps": 500,
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"global_step": 2760,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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| 2768 |
"mean_token_accuracy": 0.7488874278962612,
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| 2769 |
"num_tokens": 12776988.0,
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| 2770 |
"step": 2750
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| 2771 |
+
},
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| 2772 |
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{
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| 2773 |
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"entropy": 0.8518887549638748,
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| 2774 |
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"epoch": 0.5888,
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| 2775 |
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"grad_norm": 0.2686164677143097,
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| 2776 |
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"learning_rate": 8.295536124631385e-05,
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| 2777 |
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"loss": 0.9314091682434082,
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| 2778 |
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"mean_token_accuracy": 0.7844551488757133,
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| 2779 |
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"num_tokens": 12821354.0,
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| 2780 |
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"step": 2760
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| 2781 |
}
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| 2782 |
],
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| 2783 |
"logging_steps": 10,
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| 2797 |
"attributes": {}
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| 2798 |
}
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| 2799 |
},
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| 2800 |
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"total_flos": 6.07747536267479e+16,
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| 2801 |
"train_batch_size": 4,
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| 2802 |
"trial_name": null,
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| 2803 |
"trial_params": null
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