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 3550, 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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| 3558 |
"mean_token_accuracy": 0.7466149963438511,
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"num_tokens": 16498069.0,
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"step": 3540
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}
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],
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| 3563 |
"logging_steps": 10,
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"attributes": {}
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}
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},
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"total_flos": 7.
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| 3581 |
"train_batch_size": 4,
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| 3582 |
"trial_name": null,
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| 3583 |
"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": 0.7573333333333333,
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"eval_steps": 500,
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"global_step": 3550,
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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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| 3558 |
"mean_token_accuracy": 0.7466149963438511,
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| 3559 |
"num_tokens": 16498069.0,
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| 3560 |
"step": 3540
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| 3561 |
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},
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| 3562 |
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{
|
| 3563 |
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"entropy": 0.932567299157381,
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| 3564 |
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"epoch": 0.7573333333333333,
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| 3565 |
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"grad_norm": 0.2745480239391327,
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| 3566 |
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"learning_rate": 7.157604980736962e-05,
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| 3567 |
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"loss": 1.02783260345459,
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| 3568 |
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"mean_token_accuracy": 0.7691405609250068,
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| 3569 |
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"num_tokens": 16546746.0,
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| 3570 |
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"step": 3550
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| 3571 |
}
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| 3572 |
],
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| 3573 |
"logging_steps": 10,
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| 3587 |
"attributes": {}
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| 3588 |
}
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| 3589 |
},
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| 3590 |
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"total_flos": 7.842238964359066e+16,
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| 3591 |
"train_batch_size": 4,
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| 3592 |
"trial_name": null,
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| 3593 |
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