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 4100, 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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| 4108 |
"mean_token_accuracy": 0.7718042567372322,
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"num_tokens": 19073552.0,
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"step": 4090
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}
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],
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| 4113 |
"logging_steps": 10,
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"attributes": {}
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}
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},
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"total_flos": 9.
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| 4131 |
"train_batch_size": 4,
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"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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"epoch": 0.8746666666666667,
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"eval_steps": 500,
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"global_step": 4100,
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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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| 4108 |
"mean_token_accuracy": 0.7718042567372322,
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| 4110 |
"step": 4090
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| 4112 |
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{
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| 4113 |
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"entropy": 0.8700525127351284,
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"epoch": 0.8746666666666667,
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| 4115 |
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"grad_norm": 0.26574060320854187,
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| 4116 |
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"learning_rate": 6.265095251578796e-05,
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| 4117 |
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"loss": 0.9732645988464356,
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| 4118 |
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"mean_token_accuracy": 0.7781016409397126,
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| 4119 |
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"num_tokens": 19112840.0,
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| 4120 |
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"step": 4100
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| 4121 |
}
|
| 4122 |
],
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| 4123 |
"logging_steps": 10,
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| 4137 |
"attributes": {}
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| 4139 |
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| 4140 |
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"total_flos": 9.045065692627046e+16,
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| 4141 |
"train_batch_size": 4,
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| 4142 |
"trial_name": null,
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| 4143 |
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