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 3440, 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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"mean_token_accuracy": 0.7584069922566414,
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"num_tokens": 15984086.0,
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"step": 3430
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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": 7.
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| 3471 |
"train_batch_size": 4,
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| 3472 |
"trial_name": null,
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| 3473 |
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"best_global_step": null,
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"epoch": 0.7338666666666667,
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"global_step": 3440,
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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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| 3448 |
"mean_token_accuracy": 0.7584069922566414,
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| 3449 |
"num_tokens": 15984086.0,
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| 3450 |
"step": 3430
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| 3451 |
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| 3452 |
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{
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"entropy": 0.9371322847902774,
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| 3454 |
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"epoch": 0.7338666666666667,
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| 3455 |
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"grad_norm": 0.21763980388641357,
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| 3456 |
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"learning_rate": 7.32774073524142e-05,
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| 3457 |
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"loss": 1.0160024642944336,
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| 3458 |
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"mean_token_accuracy": 0.7715103484690189,
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| 3459 |
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"num_tokens": 16029965.0,
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| 3460 |
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"step": 3440
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| 3461 |
}
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| 3462 |
],
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| 3463 |
"logging_steps": 10,
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| 3477 |
"attributes": {}
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}
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| 3480 |
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"total_flos": 7.592043355605197e+16,
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| 3481 |
"train_batch_size": 4,
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| 3482 |
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| 3483 |
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