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 3500, 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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| 3508 |
"mean_token_accuracy": 0.7716259181499481,
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"num_tokens": 16261629.0,
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| 3510 |
"step": 3490
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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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| 3531 |
"train_batch_size": 4,
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| 3532 |
"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": 0.7466666666666667,
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"eval_steps": 500,
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"global_step": 3500,
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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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| 3508 |
"mean_token_accuracy": 0.7716259181499481,
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| 3509 |
"num_tokens": 16261629.0,
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| 3510 |
"step": 3490
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| 3511 |
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| 3512 |
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{
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| 3513 |
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"entropy": 0.9472721114754676,
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| 3514 |
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"epoch": 0.7466666666666667,
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| 3515 |
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"grad_norm": 0.2600723206996918,
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| 3516 |
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"learning_rate": 7.235342070451059e-05,
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| 3517 |
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"loss": 1.0361743927001954,
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| 3518 |
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"mean_token_accuracy": 0.761479677259922,
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| 3519 |
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"num_tokens": 16308149.0,
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| 3520 |
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"step": 3500
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| 3521 |
}
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| 3522 |
],
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| 3523 |
"logging_steps": 10,
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| 3537 |
"attributes": {}
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| 3538 |
}
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| 3539 |
},
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| 3540 |
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"total_flos": 7.724771959780147e+16,
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| 3541 |
"train_batch_size": 4,
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| 3542 |
"trial_name": null,
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| 3543 |
"trial_params": null
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