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 3750, 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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| 3758 |
"mean_token_accuracy": 0.7630825422704219,
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"num_tokens": 17421511.0,
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| 3760 |
"step": 3740
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}
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],
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| 3763 |
"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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| 3781 |
"train_batch_size": 4,
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| 3782 |
"trial_name": null,
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| 3783 |
"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": 0.8,
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"eval_steps": 500,
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"global_step": 3750,
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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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| 3758 |
"mean_token_accuracy": 0.7630825422704219,
|
| 3759 |
"num_tokens": 17421511.0,
|
| 3760 |
"step": 3740
|
| 3761 |
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},
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| 3762 |
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{
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| 3763 |
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"entropy": 1.0029884599149228,
|
| 3764 |
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"epoch": 0.8,
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| 3765 |
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"grad_norm": 0.23356133699417114,
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| 3766 |
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"learning_rate": 6.840429660536953e-05,
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| 3767 |
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"loss": 1.0578575134277344,
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| 3768 |
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"mean_token_accuracy": 0.7524963855743408,
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| 3769 |
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"num_tokens": 17474234.0,
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| 3770 |
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"step": 3750
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| 3771 |
}
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| 3772 |
],
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| 3773 |
"logging_steps": 10,
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| 3787 |
"attributes": {}
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| 3788 |
}
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| 3789 |
},
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| 3790 |
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"total_flos": 8.272621480088371e+16,
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| 3791 |
"train_batch_size": 4,
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| 3792 |
"trial_name": null,
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| 3793 |
"trial_params": null
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