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 2450, 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": 0.7516932919621467,
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"num_tokens": 11350668.0,
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"step": 2440
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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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| 2481 |
"train_batch_size": 4,
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| 2482 |
"trial_name": null,
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"trial_params": null
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"best_global_step": null,
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"epoch": 0.5226666666666666,
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"global_step": 2450,
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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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| 2458 |
"mean_token_accuracy": 0.7516932919621467,
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| 2459 |
"num_tokens": 11350668.0,
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| 2460 |
"step": 2440
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| 2461 |
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| 2462 |
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{
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| 2463 |
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"entropy": 1.0364744253456593,
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| 2464 |
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"epoch": 0.5226666666666666,
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| 2465 |
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"grad_norm": 0.24485838413238525,
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| 2466 |
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"learning_rate": 8.67929811055542e-05,
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| 2467 |
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"loss": 1.100508689880371,
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| 2468 |
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"mean_token_accuracy": 0.7447643153369427,
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| 2469 |
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"num_tokens": 11403181.0,
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| 2470 |
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"step": 2450
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| 2471 |
}
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| 2472 |
],
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"logging_steps": 10,
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| 2487 |
"attributes": {}
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| 2488 |
}
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},
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| 2490 |
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"total_flos": 5.408470279940198e+16,
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| 2491 |
"train_batch_size": 4,
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"trial_name": null,
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