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 3810, 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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| 3818 |
"mean_token_accuracy": 0.7626087903976441,
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"num_tokens": 17705375.0,
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| 3820 |
"step": 3800
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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": 8.
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| 3841 |
"train_batch_size": 4,
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| 3842 |
"trial_name": null,
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| 3843 |
"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": 0.8128,
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"eval_steps": 500,
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"global_step": 3810,
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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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| 3818 |
"mean_token_accuracy": 0.7626087903976441,
|
| 3819 |
"num_tokens": 17705375.0,
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| 3820 |
"step": 3800
|
| 3821 |
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},
|
| 3822 |
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{
|
| 3823 |
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"entropy": 1.0885871052742004,
|
| 3824 |
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"epoch": 0.8128,
|
| 3825 |
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"grad_norm": 0.24882915616035461,
|
| 3826 |
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"learning_rate": 6.743487459046971e-05,
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| 3827 |
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"loss": 1.1456743240356446,
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| 3828 |
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"mean_token_accuracy": 0.7413103066384792,
|
| 3829 |
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"num_tokens": 17751890.0,
|
| 3830 |
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"step": 3810
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| 3831 |
}
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| 3832 |
],
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| 3833 |
"logging_steps": 10,
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| 3847 |
"attributes": {}
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| 3848 |
}
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| 3849 |
},
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| 3850 |
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"total_flos": 8.405295111864422e+16,
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| 3851 |
"train_batch_size": 4,
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| 3852 |
"trial_name": null,
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| 3853 |
"trial_params": null
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