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 2460, 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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| 2468 |
"mean_token_accuracy": 0.7447643153369427,
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"num_tokens": 11403181.0,
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| 2470 |
"step": 2450
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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": 5.
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| 2491 |
"train_batch_size": 4,
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| 2492 |
"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": 0.5248,
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"global_step": 2460,
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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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| 2468 |
"mean_token_accuracy": 0.7447643153369427,
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| 2469 |
"num_tokens": 11403181.0,
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| 2470 |
"step": 2450
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| 2471 |
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| 2472 |
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{
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| 2473 |
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"entropy": 0.8236982800066471,
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| 2474 |
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"epoch": 0.5248,
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| 2475 |
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"grad_norm": 0.28031599521636963,
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| 2476 |
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"learning_rate": 8.667556834990211e-05,
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| 2477 |
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"loss": 0.9254312515258789,
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| 2478 |
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"mean_token_accuracy": 0.7904586613178253,
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| 2479 |
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"num_tokens": 11443565.0,
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| 2480 |
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"step": 2460
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| 2481 |
}
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| 2482 |
],
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| 2483 |
"logging_steps": 10,
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"attributes": {}
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}
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},
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"total_flos": 5.427367267358515e+16,
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| 2501 |
"train_batch_size": 4,
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"trial_name": null,
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