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 3400, 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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| 3408 |
"mean_token_accuracy": 0.7475218966603279,
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"num_tokens": 15789887.0,
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| 3410 |
"step": 3390
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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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| 3431 |
"train_batch_size": 4,
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| 3432 |
"trial_name": null,
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| 3433 |
"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": 0.7253333333333334,
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"eval_steps": 500,
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"global_step": 3400,
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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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| 3408 |
"mean_token_accuracy": 0.7475218966603279,
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| 3409 |
"num_tokens": 15789887.0,
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| 3410 |
"step": 3390
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| 3411 |
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},
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| 3412 |
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{
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| 3413 |
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"entropy": 1.0159111820161342,
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| 3414 |
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"epoch": 0.7253333333333334,
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| 3415 |
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"grad_norm": 0.2403489053249359,
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| 3416 |
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"learning_rate": 7.38878451162126e-05,
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| 3417 |
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"loss": 1.1378083229064941,
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| 3418 |
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"mean_token_accuracy": 0.7544682174921036,
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| 3419 |
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"num_tokens": 15837848.0,
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| 3420 |
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"step": 3400
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| 3421 |
}
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| 3422 |
],
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| 3423 |
"logging_steps": 10,
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| 3437 |
"attributes": {}
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| 3438 |
}
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| 3439 |
},
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| 3440 |
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"total_flos": 7.502343720778445e+16,
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| 3441 |
"train_batch_size": 4,
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| 3442 |
"trial_name": null,
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| 3443 |
"trial_params": null
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