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 3710, 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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| 3718 |
"mean_token_accuracy": 0.7787635132670403,
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"num_tokens": 17235554.0,
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| 3720 |
"step": 3700
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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": 8.
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| 3741 |
"train_batch_size": 4,
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| 3742 |
"trial_name": null,
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| 3743 |
"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": 0.7914666666666667,
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"eval_steps": 500,
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"global_step": 3710,
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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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| 3718 |
"mean_token_accuracy": 0.7787635132670403,
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| 3719 |
"num_tokens": 17235554.0,
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| 3720 |
"step": 3700
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| 3721 |
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},
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| 3722 |
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{
|
| 3723 |
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"entropy": 0.8578987941145897,
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| 3724 |
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"epoch": 0.7914666666666667,
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| 3725 |
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"grad_norm": 0.2751041352748871,
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| 3726 |
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"learning_rate": 6.904619356135484e-05,
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| 3727 |
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"loss": 0.9659609794616699,
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| 3728 |
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"mean_token_accuracy": 0.7794149458408356,
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| 3729 |
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"num_tokens": 17280617.0,
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| 3730 |
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"step": 3710
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| 3731 |
}
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| 3732 |
],
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| 3733 |
"logging_steps": 10,
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"attributes": {}
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| 3748 |
}
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| 3749 |
},
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| 3750 |
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"total_flos": 8.182288310893978e+16,
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| 3751 |
"train_batch_size": 4,
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| 3752 |
"trial_name": null,
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| 3753 |
"trial_params": null
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