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 2840, 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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| 2848 |
"mean_token_accuracy": 0.7598815195262432,
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"num_tokens": 13163748.0,
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"step": 2830
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}
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],
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| 2853 |
"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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| 2871 |
"train_batch_size": 4,
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| 2872 |
"trial_name": null,
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"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": 0.6058666666666667,
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"eval_steps": 500,
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"global_step": 2840,
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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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| 2848 |
"mean_token_accuracy": 0.7598815195262432,
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| 2849 |
"num_tokens": 13163748.0,
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| 2850 |
"step": 2830
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| 2851 |
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},
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| 2852 |
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{
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| 2853 |
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"entropy": 0.8110849797725678,
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| 2854 |
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"epoch": 0.6058666666666667,
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| 2855 |
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"grad_norm": 0.3148553967475891,
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| 2856 |
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"learning_rate": 8.190159423236086e-05,
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| 2857 |
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"loss": 0.8950259208679199,
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| 2858 |
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"mean_token_accuracy": 0.7862283095717431,
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| 2859 |
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"num_tokens": 13204391.0,
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| 2860 |
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"step": 2840
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| 2861 |
}
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],
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| 2863 |
"logging_steps": 10,
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"attributes": {}
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| 2878 |
}
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"total_flos": 6.256929604727194e+16,
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| 2881 |
"train_batch_size": 4,
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"trial_name": null,
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