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 2810, 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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| 2818 |
"mean_token_accuracy": 0.7694585740566253,
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"num_tokens": 13015439.0,
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"step": 2800
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}
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],
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"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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| 2841 |
"train_batch_size": 4,
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| 2842 |
"trial_name": null,
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| 2843 |
"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": 0.5994666666666667,
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"eval_steps": 500,
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"global_step": 2810,
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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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| 2818 |
"mean_token_accuracy": 0.7694585740566253,
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| 2819 |
"num_tokens": 13015439.0,
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| 2820 |
"step": 2800
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| 2821 |
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},
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| 2822 |
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{
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| 2823 |
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"entropy": 1.0109743446111679,
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| 2824 |
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"epoch": 0.5994666666666667,
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| 2825 |
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"grad_norm": 0.299020379781723,
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| 2826 |
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"learning_rate": 8.229966720757007e-05,
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| 2827 |
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"loss": 1.1124341011047363,
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| 2828 |
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"mean_token_accuracy": 0.7469129160046577,
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| 2829 |
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"num_tokens": 13064583.0,
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| 2830 |
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"step": 2810
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| 2831 |
}
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| 2832 |
],
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| 2833 |
"logging_steps": 10,
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| 2847 |
"attributes": {}
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| 2848 |
}
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| 2849 |
},
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"total_flos": 6.191695390971187e+16,
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| 2851 |
"train_batch_size": 4,
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| 2852 |
"trial_name": null,
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| 2853 |
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